The growing impact of the ''analytics'' perspective in recent years, which integrates advanced data-mining and learning methods, is often associated with increasing access to large databases and with decision support systems. Since its origin, the field of analytics has been strongly business-oriented, with a typical focus on data-driven decision processes. In public decisions, however, issues such as individual and social values, culture and public engagement are more important and, to a large extent, characterise the policy cycle of design, testing, implementation, evaluation and review of public policies. Therefore public policy making seems to be a much more socially complex process than has hitherto been considered by most analytics methods and applications. In this paper, we thus suggest a framework for the use of analytics in supporting the policy cycle-and conceptualise it as ''Policy Analytics''.Keywords Analytics Á Policy analysis Á Decision analysis Á Policy cycle Á Decision support
The paper aims at addressing the problem of what makes specific aiding to decide within public policy making problem situations. Under such a perspective it analyses some basic concepts such as "public policy", "deliberation", "legitimation", "accountability" and shows the necessity to expand the concept of rationality which is expected to be behind the acceptability of a public policy. We then analyse the more recent tentative to construct a rational support to policy making, that is the "evidence-based policy making" approach. Despite the innovation introduced with this approach, we show that it basically fails to address the deep reasons for which supporting the design, implementation and assessment of public policies is a hard problem. We finally show that we need to move one step ahead, specialising decision aiding methodology to meet the policy cycle requirements: a demand for policy analytics.
In our cities, the production and consumption of resources are achieved at an unsustainable rate. Combined with an increasing global population and accelerating urbanization, the absence of a new approach will almost certainly have dramatic environmental consequences. Potential solutions are emerging: the concepts of circular economy (CE) and urban metabolism (UM), which contrast the current and traditional linear extract-produce-use-dispose model of the modern economic and urban systems, offer a new approach. In this Primer, we present the principles of CE and UM as well as their origins and definitions, strengths and weaknesses, similarities, and limits. We introduce how these concepts can be used for designing a new urban framework called circular urban metabolism (CUM), which encourages urban planners and decision makers to study, design, and manage sustainable cities. CUM has the potential to unite research fields to promote collaboration across disciplines that operate on the planning, design, and management of cities and their complexities.
To build resilient and climate-neutral cities, it is required to modify current territorial planning processes to make them more sustainable and virtuous. However, the implementation of new strategies and innovative governance models faces multiple obstacles, economic restrictions, and technical gaps. In particular, local governments often find it difficult to build structured transition processes. This article investigates how it is possible to respond effectively to the need of urban contexts to adapt to climate impacts, analyzing the case of the Climate Transition Strategy (CTS) “La Brianza Cambia Clima”, the first in Italy of this kind. Through the technical framework and the methodology described, the CTS can activate inter-municipal transformative actions through the mainstreaming of planning tools, the construction of a medium-long-term vision, and the identification of concrete and widespread actions to be implemented in the territory. This coordinated and shared strategic approach allows one to give stability, coherence, and continuity to adaptation processes involving different stakeholders and sectors of the Public Administration. Finally, it favors the implementation of multidisciplinary policies for territorial resilience on a large scale.
Circular economy and urban metabolism concepts have recently received great attention both in the political and academic arenas, starting a roll-over process of the "take, make, and dispose" dominant economic model that is leading to an ongoing increase of resource consumption and waste generation. However, there is a relative lack of guidelines for introducing such concepts in a decision-making process able to support the design of appropriate policies and strategies and the definition of specific actions to cope with such challenges. This paper attempts to contribute to the recent efforts at incorporating these concepts in policy and decision-making processes by providing a methodology for the development of strategic plans for waste prevention and resource management. The proposed methodology, developed within the Urban_WINS project, combines different quantitative-analytical and qualitative methods and tools, together with a participatory process. The methodology was tested in eight EU cities and allowed to formulate several measures and actions aimed at addressing the challenges posed by the current consumption patterns. Moreover, the participatory approach led to the legitimization of the strategic plans, as well as to raise awareness among stakeholders. Although it might require specific tailor-made adjustments, this methodology is suitable to be replicated in other contexts.
Urban and peri-urban areas are subject to major societal challenges, like food security, climate change, biodiversity, resource efficiency, land management, social cohesion, and economic growth. In that context, Urban and Peri-urban Agriculture (UPA), thanks to its multifunctionality, could have a high value in providing social, economic, and environmental co-benefits. UPA is an emerging field of research and production that aims to improve food security and climate change impact reduction, improving urban resilience and sustainability. In this paper, a replicable GIS-based approach was used to localize and quantify available areas for agriculture, including both flat rooftop and ground-level areas in the mainland of the city of Venice (Italy). Then, possible horticultural yield production was estimated considering common UPA yield value and average Italian consumption. Climate change mitigation, like CO2 reduction and sequestration, and climate change adaptation, like Urban Flooding and Urban Heat Island reduction, due to the new UPA areas’ development were estimated. Despite the urban density, the identified areas have the potential to produce enough vegetables for the residents and improve climate change mitigation and adaptation, if transformed into agricultural areas. Finally, the paper concludes with a reflection on the co-benefits of UPA multifunctionality, and with some policy suggestions.
The adversities of climate change represent a serious risk factor on both food production, rural territories and landscapes. In light of these irreversible trends, the process of adaptation of the rural territory is a necessary step, in order to increase its climate resilience. In this study, the vulnerability assessment was the tool used to evaluate the specific phenomenon of “flooding and backwatering” in the case study of Emilia Romagna region (Italy). The approach was based on the IPCC’s risk analysis methodology, populated by different layers regarding specifical proxies related to the adaptive capacity and the sensitivity of the territory to water stagnation, then we assessed with the normalization process of the different information levels. The aim of the research consisted in the realization of a regional map of the vulnerability to floods and backwaters, in order to rank the territory to this specific phenomenon. The final result could be useful both for the relationship with planning choices and for local-based actions in agricultural policies that in Italy are taken at regional level.
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