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International audience ; Due to the disparity of interests associated with a shared resource, the political dimension of contemporary water management is an important factor in conflicts among stakeholders. In this sense, environmental decision-making takes place in a highly interconnected system, in which neither the decisional ramifications nor the complexity of its impacts, can be neglected. The Mediterranean Region is characterized by water scarcity. This problem is increasingly challenging human and more-than-human communities, developing the need of a dynamic support in complex decision-making processes. A Multi-Agent System approach and System Dynamics modelling can introduce unconventional alternatives that can combine physical and economical components, with the consequences of individual behaviors in the management of a common resource, namely water. The paper works on analysis carried out in the irrigation water management in the Apulia region and a case-based modelling approach is suggested.

International audience ; Due to the disparity of interests associated with a shared resource, the political dimension of contemporary water management is an important factor in conflicts among stakeholders. In this sense, environmental decision-making takes place in a highly interconnected system, in which neither the decisional ramifications nor the complexity of its impacts, can be neglected. The Mediterranean Region is characterized by water scarcity. This problem is increasingly challenging human and more-than-human communities, developing the need of a dynamic support in complex decision-making processes. A Multi-Agent System approach and System Dynamics modelling can introduce unconventional alternatives that can combine physical and economical components, with the consequences of individual behaviors in the management of a common resource, namely water. The paper works on analysis carried out in the irrigation water management in the Apulia region and a case-based modelling approach is suggested.

AbstractSystem dynamics (SD) models are commonly used for structuring complex problems to support decision‐making. They are used to investigate areas in which limited knowledge is available, describing nonlinear relationships and including intangible elements. Although this explorative nature is one of the key advantages, it also represents a challenge for quantifying the intangible, i.e. more qualitative aspects of an SD model, especially when it is not possible to apply conventional analytical methods due to data scarcity. Procedures to obtain and analyse information using participatory approaches are limited. First, this article outlines existing quantification methods and related open questions when dealing with soft variables and data scarcity. Secondly, it summarises the quantification process developed during a participatory SD process, describing how we dealt with data scarcity and soft variables. Lastly, we suggest a quantification framework in relation to data availability and level of stakeholder engagement. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

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.

The current transformations in society, the economy and the public sector call for the development of more unified theoretical frameworks. This article takes the literature on strategic management as a theoretical entry angle and aims to better understand how the adoption of models of strategic management can enable processes of public value co-creation. Utilising the literature centred on the notion of 'schools of thought' in the strategic management of public services, the article discusses how co-creation as a mode of governance in public services can contribute to innovative public service solutions and value co-creation. The Welsh Water's 'Water Resilient Community' – a project characterised by long-term strategic planning as well as by local innovation – is used to illustrate the argument. Four propositions on the drivers/enablers and key managerial issues for undertaking a strategic approach to co-creation as a mode of governance are offered to enhance future practice, research and theory.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.