Multicriteria Decision Analysis in Group Decision Processes

Framing Algorithm-Driven Development of Sets of Objectives Using Elementary Interactions

Multi-criteria decision analysis (MCDA) is an established methodology to support the decision-making of multi-objective problems. For conducting an MCDA, in most cases, a set of objectives (SOO) is required, which consists of a hierarchical structure comprised of objectives, criteria, and indicators. The development of an SOO is usually based on moderated development processes requiring high organizational and cognitive effort from all stakeholders involved. This article proposes elementary interactions as a key paradigm of an algorithm-driven development process for an SOO that requires little moderation efforts. Elementary interactions are self-contained information requests that may be answered with little cognitive effort. The pairwise comparison of elements in the well-known analytical hierarchical process (AHP) is an example of an elementary interaction. Each elementary interaction in the development process presented contributes to the stepwise development of an SOO. Based on the hypothesis that an SOO may be developed exclusively using elementary interactions (EIs), a concept for a multi-user platform is proposed. Essential components of the platform are a Model Aggregator, an Elementary Interaction Stream Generator, a Participant Manager, and a Discussion Forum. While the latter component serves the professional exchange of the participants, the first three components are intended to be automatable by algorithms. The platform concept proposed has been evaluated partly in an explorative validation study demonstrating the general functionality of the algorithms outlined. In summary, the platform concept suggested demonstrates the potential to ease SOO development processes as the platform concept does not restrict the application domain; it is intended to work with little administration moderation efforts, and it supports the further development of an existing SOO in the event of changes in external conditions. The algorithm-driven development of SOOs proposed in this article may ease the development of MCDA applications and, thus, may have a positive effect on the spread of MCDA applications.

A Framework for Ethical Research and Innovation

In this contribution, we set out a framework for ethical research and innovation. Our framework draws upon recent scholarly work recommending the introduction of new models at the intersection of ethics, strategy, and science and technology studies to inform and explicate how the decisions of researchers can be considered ethical. Ethical research and innovation is construed in our framework as a dynamic process emerging from decisions of multiple stakeholders in innovation ecosystems prior to, during and after the execution of a research and innovation project. The framework can be used by different types of research organizations to implement governance models of ethical research and innovation.

Identification of Protective Actions to Reduce the Vulnerability of Safety-Critical Systems to Malevolent Intentional Acts: An Optimization-Based Decision-Making Approach

An empirical classification model based on the Majority Rule Sorting (MR-Sort) method has been previously proposed by the authors to evaluate the vulnerability of safety-critical systems (in particular, nuclear power plants [NPPs]) with respect to malevolent intentional acts. In this article, the model serves as the basis for an analysis aimed at determining a set of protective actions to be taken (e.g., increasing the number of monitoring devices, reducing the number of accesses to the safety-critical system) in order to effectively reduce the level of vulnerability of the safety-critical systems under consideration. In particular, the problem is here tackled within an optimization framework: the set of protective actions to implement is chosen as the one minimizing the overall level of vulnerability of a group of safety-critical systems. In this context, three different optimization approaches have been explored: (i) one single classification model is built to evaluate and minimize system vulnerability; (ii) an ensemble of compatible classification models, generated by the bootstrap method, is employed to perform a "robust" optimization, taking as reference the "worst-case" scenario over the group of models; (iii) finally, a distribution of classification models, still obtained by bootstrap, is considered to address vulnerability reduction in a "probabilistic" fashion (i.e., by minimizing the "expected" vulnerability of a fleet of systems). The results are presented and compared with reference to a fictitious example considering NPPs as the safety-critical systems of interest.

Public Initiatives of Settlement Transformation: A Theoretical-Methodological Approach to Selecting Tools of Multi-Criteria Decision Analysis

In Europe, the operating context in which initiatives of settlement transformation are currently initiated is characterized by a complex, elaborate combination of technical, regulatory and governance-related factors. A similar set of considerations makes it necessary to address the complex decision-making problems to be resolved through multidisciplinary, comparative approaches designed to rationalize the process and treat the elements to be considered in systematic fashion with respect to the range of alternatives available as solutions. Within a context defined in this manner, decision-making processes must often be used to obtain multidisciplinary and multidimensional analyses to support the choices made by the decision-makers. Such analyses are carried out using multi-criteria tools designed to arrive at syntheses of the numerous forms of input data needed to describe decision-making problems of similar complexity, so that one or more outcomes of the synthesis make possible informed, well thought-out, strategic decisions. The technical literature on the topic proposes numerous tools of multi-criteria analysis for application in different decision-making contexts. Still, no specific contributions have been drawn up to date on the approach to take in selecting the tool best suited to providing adequate responses to the queries of evaluation that arise most frequently in the various fields of application, and especially in the settlement sector. The objective of this paper is to propose, by formulating a taxonomy of the endogenous and exogenous variables of tools of multi-criteria analysis, a methodology capable of selecting the tool best suited to the queries of evaluation which arise regarding the chief categories of decision-making problems, and particularly in the settlement sector.

Decision theory and the evaluation of risks and benefits of clinical trials

Research ethics committees (RECs) are tasked to assess the risks and the benefits of a clinical trial. In previous studies, it was shown that RECs find this task difficult, if not impossible, to do. The current approaches to benefit-risk assessment (i.e. Component Analysis and the Net Risk Test) confound the various risk-benefit tasks, and as such, make balancing impossible. In this article, we show that decision theory, specifically through the expected utility theory and multiattribute utility theory, enable for an explicit and ethically weighted risk-benefit evaluation. This makes a balanced ethical justification possible, and thus a more rationally defensible decision making.