Suchergebnisse

AbstractIn this article, we argue that the term "sorting" (in MCDA), although established within a well‐defined community, is unappropriate for linguistic, scientific and pragmatic reasons. We present and discuss such reasons and we suggest the use of the term "rating", since fitting better both the foundational part of this class of methods and the necessity to improve the visibility of our community.

International audience ; Decision support is the science and associated practice that consist in providing recommendations to decision makers facing problems, based on available theoretical knowledge and empirical data. Although this activity is often seen as being mainly concerned with solving mathematical problems and conceiving algorithms, it is essentially an empirical and socially framed activity, where interactions between clients and analysts, and between them and concerned third parties, play a crucial role. Since the 80s', two concepts have structured the literature devoted to analysing this aspect of decision support: validity and legitimacy. Whereas validity is focused on the interactions between the client and the analyst, legitimacy refers to the broader picture: the organisational context, the overall problem situation, the environment, culture, history. Despite its unmistakable importance, this concept has not received the attention it deserves in the literature in operational research and decision support. The present chapter aims at filling this gap. For that purpose, we review the literature in other disciplines (mainly philosophy and political science) that is demonstrably relevant to elaborate a concept of legitimacy useful in decision support contexts. Based on this review, we propose a general theory of legitimacy, adapted to decision support contexts, encompassing the relevant contributions we found in the literature. According to this general theory, a legitimate decision support intervention is one for which the decision support provider produces a justification that satisfies two conditions: (i) it effectively convinces the decision support provider's interlocutors (effectiveness condition) and (ii) it is organised around the active elicitation of as many and as diverse counterarguments as possible (truthfulness condition). Despite its conceptual simplicity, legitimacy, understood in this sense, is a very exacting requirement, opening ambitious research avenues that we delineate.

International audience ; Decision support is the science and associated practice that consist in providing recommendations to decision makers facing problems, based on available theoretical knowledge and empirical data. Although this activity is often seen as being mainly concerned with solving mathematical problems and conceiving algorithms, it is essentially an empirical and socially framed activity, where interactions between clients and analysts, and between them and concerned third parties, play a crucial role. Since the 80s', two concepts have structured the literature devoted to analysing this aspect of decision support: validity and legitimacy. Whereas validity is focused on the interactions between the client and the analyst, legitimacy refers to the broader picture: the organisational context, the overall problem situation, the environment, culture, history. Despite its unmistakable importance, this concept has not received the attention it deserves in the literature in operational research and decision support. The present chapter aims at filling this gap. For that purpose, we review the literature in other disciplines (mainly philosophy and political science) that is demonstrably relevant to elaborate a concept of legitimacy useful in decision support contexts. Based on this review, we propose a general theory of legitimacy, adapted to decision support contexts, encompassing the relevant contributions we found in the literature. According to this general theory, a legitimate decision support intervention is one for which the decision support provider produces a justification that satisfies two conditions: (i) it effectively convinces the decision support provider's interlocutors (effectiveness condition) and (ii) it is organised around the active elicitation of as many and as diverse counterarguments as possible (truthfulness condition). Despite its conceptual simplicity, legitimacy, understood in this sense, is a very exacting requirement, opening ambitious research avenues that we delineate.

International audience ; Decision support is the science and associated practice that consist in providing recommendations to decision makers facing problems, based on available theoretical knowledge and empirical data. Although this activity is often seen as being mainly concerned with solving mathematical problems and conceiving algorithms, it is essentially an empirical and socially framed activity, where interactions between clients and analysts, and between them and concerned third parties, play a crucial role. Since the 80s', two concepts have structured the literature devoted to analysing this aspect of decision support: validity and legitimacy. Whereas validity is focused on the interactions between the client and the analyst, legitimacy refers to the broader picture: the organisational context, the overall problem situation, the environment, culture, history. Despite its unmistakable importance, this concept has not received the attention it deserves in the literature in operational research and decision support. The present chapter aims at filling this gap. For that purpose, we review the literature in other disciplines (mainly philosophy and political science) that is demonstrably relevant to elaborate a concept of legitimacy useful in decision support contexts. Based on this review, we propose a general theory of legitimacy, adapted to decision support contexts, encompassing the relevant contributions we found in the literature. According to this general theory, a legitimate decision support intervention is one for which the decision support provider produces a justification that satisfies two conditions: (i) it effectively convinces the decision support provider's interlocutors (effectiveness condition) and (ii) it is organised around the active elicitation of as many and as diverse counterarguments as possible (truthfulness condition). Despite its conceptual simplicity, legitimacy, understood in this sense, is a very exacting requirement, opening ambitious research avenues that we delineate.

AbstractGenerating alternatives for decision problems is a critical activity regularly underestimated and underdeveloped in the decision analysis literature. We present a survey showing how little this topic has been studied in the last 50 years. We then introduce a general framework under which formalize the design of alternatives. Two examples help to understand our point of view: alternatives are generated through separation of attributes describing the value space of the client/decision maker.

International audience ; The design of alternatives is an essential part of decision making that has been less studied in theory and practice compared to alternatives' evaluation. This topic is particularly relevant in the context of public policy making, where policy design represents a crucial step of the policy cycle since it determines the quality of the alternative policies being considered. This paper attempts to formalise the decision aiding process in two real interventions dealing with alternatives' generation for territorial policy making in Italy. The aim of this research is to understand what generates novelty within the alternatives' design phase of a decision aiding process, i.e. what allows to expand the solution space and discover new alternatives to solve the problem under consideration. It demonstrates ways in which novelty in decision processes can be supported by Operational Research/Multicriteria Decision Aiding tools. The two case studies are used to answer the following questions: (i) Why have new alternatives arose during the policy making process? (ii) How have they been generated? (iii) Which consequences did they lead to? and (iv) What generated novelty in the process? The results highlight two main reasons that can expand the solution space within a decision aiding process: (i) dissatisfaction (of the client, of the analyst or of the relevant stakeholders, especially when dealing with public policies) with respect to the solutions currently proposed to the decision making problem and (ii) opportunity for a change in one of the variables/constraints.

International audience ; The design of alternatives is an essential part of decision making that has been less studied in theory and practice compared to alternatives' evaluation. This topic is particularly relevant in the context of public policy making, where policy design represents a crucial step of the policy cycle since it determines the quality of the alternative policies being considered. This paper attempts to formalise the decision aiding process in two real interventions dealing with alternatives' generation for territorial policy making in Italy. The aim of this research is to understand what generates novelty within the alternatives' design phase of a decision aiding process, i.e. what allows to expand the solution space and discover new alternatives to solve the problem under consideration. It demonstrates ways in which novelty in decision processes can be supported by Operational Research/Multicriteria Decision Aiding tools. The two case studies are used to answer the following questions: (i) Why have new alternatives arose during the policy making process? (ii) How have they been generated? (iii) Which consequences did they lead to? and (iv) What generated novelty in the process? The results highlight two main reasons that can expand the solution space within a decision aiding process: (i) dissatisfaction (of the client, of the analyst or of the relevant stakeholders, especially when dealing with public policies) with respect to the solutions currently proposed to the decision making problem and (ii) opportunity for a change in one of the variables/constraints.