40,628 research outputs found

    Organic Farming in Europe by 2010: Scenarios for the future

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    How will organic farming in Europe evolve by the year 2010? The answer provides a basis for the development of different policy options and for anticipating the future relative competitiveness of organic and conventional farming. The authors tackle the question using an innovative approach based on scenario analysis, offering the reader a range of scenarios that encompass the main possible evolutions of the organic farming sector. This book constitutes an innovative and reliable decision-supporting tool for policy makers, farmers and the private sector. Researchers and students operating in the field of agricultural economics will also benefit from the methodological approach adopted for the scenario analysis

    Operationalizing the circular city model for naples' city-port: A hybrid development strategy

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    The city-port context involves a decisive reality for the economic development of territories and nations, capable of significantly influencing the conditions of well-being and quality of life, and of making the Circular City Model (CCM) operational, preserving and enhancing seas and marine resources in a sustainable way. This can be achieved through the construction of appropriate production and consumption models, with attention to relations with the urban and territorial system. This paper presents an adaptive decision-making process for Naples (Italy) commercial port's development strategies, aimed at re-establishing a sustainable city-port relationship and making Circular Economy (CE) principles operative. The approach has aimed at implementing a CCM by operationalizing European recommendations provided within both the Sustainable Development Goals (SDGs) framework-specifically focusing on goals 9, 11 and 12-and the Maritime Spatial Planning European Directive 2014/89, to face conflicts about the overlapping areas of the city-port through multidimensional evaluations' principles and tools. In this perspective, a four-step methodological framework has been structured applying a place-based approach with mixed evaluation methods, eliciting soft and hard knowledge domains, which have been expressed and assessed by a core set of Sustainability Indicators (SI), linked to SDGs. The contribution outcomes have been centred on the assessment of three design alternatives for the East Naples port and the development of a hybrid regeneration scenario consistent with CE and sustainability principles. The structured decision-making process has allowed us to test how an adaptive approach can expand the knowledge base underpinning policy design and decisions to achieve better outcomes and cultivate a broad civic and technical engagement, that can enhance the legitimacy and transparency of policies

    Using Data Envelopment Analysis to Assess the Relative Efficiency of Different Climate Policy Portfolios

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    Within the political, scientific and economic debate on climate change, the process of evaluating climate policies ex-ante, during and/or ex-post their lifetime, is receiving increasing attention from international institutions and organisations. The task becomes particularly challenging when the aim is to evaluate strategies or policies from a sustainability perspective. The three pillars of sustainability should then be jointly considered in the evaluation process, thus enabling a comparison of the social, the environmental and the economic dimensions of the policy’s impact. This is commonly done in a qualitative manner and is often based on subjective procedures. The present paper discusses a data-based, quantitative methodology to assess the relative performances of different climate policies, when long term economic, social and environmental impacts of the policy are considered. The methodology computes competitive advantages as well as relative efficiencies of climate policies and is here presented through an application to a sample of eleven global climate policies, considered as plausible for the near future. The proposed procedure is based on Data Envelopment Analysis (DEA), a technique commonly employed in evaluating the relative efficiency of a set of decision making units. We consider here two possible applications of DEA. In the first, DEA is applied coupled with Cost-Benefit Analysis (CBA) in order to evaluate the comparative advantages of policies when accounting for social and environmental impacts, as well as net economic benefits. In the second, DEA is applied to compute a relative efficiency score, which accounts for environmental and social benefits and costs interpreted as outputs and inputs. Although the choice of the model used to simulate future economic and environmental implications of each policy (in the present paper we use the FEEM RICE model), as well as the choice of indicators for costs and benefits, represent both arbitrary decisions, the methodology presented is shown to represent a practical tool to be flexibly adopted by decision makers in the phase of policy design.Climate, Policy, Valuation, Data envelopment analysis, Sustainability

    A Review of Recent Studies on Cost Effectiveness of GHG Mitigation Measures in the European Agro-Forestry Sector

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    Over the last twenty years, climate change has become an increasing concern for scientists, public opinions and policy makers. Due to the pervasive nature of its impacts for many important aspects of human life, climate change is likely to influence and be influenced by the most diverse policy or management choices. This is particularly true for those interventions affecting agriculture and forestry: they are strongly dependent on climate phenomena, but also contribute to climate evolution being sources of and sinks for greenhouse gases. This paper offers a survey of the existing literature assessing cost, effectiveness and efficiency of greenhouse gas mitigation strategies, or broader economic reforms, targeted to the agricultural and forestry sectors. The specific focus is on European Countries. Different methodological approaches, research questions addressed and results are examined. The main finding is that agriculture and forestry can potentially provide GHG reduction at a competitive cost. Nevertheless this cost is positive; accordingly, mitigation policies should be carefully designed either to balance costs with expected benefits or to avoid excessive penalisation of the sectors involved. Finally needs are highlighted for improving the existing knowledge and research methodologies.Agriculture, Forestry, Climate Change, Greenhouse Gases, Policy Measures, Cost-Effectiveness, Meacap

    Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction

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    Assessing systemic risk in financial markets is of great importance but it often requires data that are unavailable or available at a very low frequency. For this reason, systemic risk assessment with partial information is potentially very useful for regulators and other stakeholders. In this paper we consider systemic risk due to fire sales spillover and portfolio rebalancing by using the risk metrics defined by Greenwood et al. (2015). By using the Maximum Entropy principle we propose a method to assess aggregated and single bank's systemicness and vulnerability and to statistically test for a change in these variables when only the information on the size of each bank and the capitalization of the investment assets are available. We prove the effectiveness of our method on 2001-2013 quarterly data of US banks for which portfolio composition is available.Comment: 36 pages, 6 figures, Accepted on Journal of Economic Dynamics and Contro

    A problem-structuring model for analyzing transportation–environment relationships

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    This is the post-print version of the final paper published in European Journal of Operational Research. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.This study discusses a decision support framework that guides policy makers in their strategic transportation related decisions by using multi-methodology. For this purpose, a methodology for analyzing the effects of transportation policies on environment, society, economy, and energy is proposed. In the proposed methodology, a three-stage problem structuring model is developed. Initially, experts’ opinions are structured by using a cognitive map to determine the relationships between transportation and environmental concepts. Then a structural equation model (SEM) is constructed, based on the cognitive map, to quantify the relations among external transportation and environmental factors. Finally the results of the SEM model are used to evaluate the consequences of possible policies via scenario analysis. In this paper a pilot study that covers only one module of the whole framework, namely transportation–environment interaction module, is conducted to present the applicability and usefulness of the methodology. This pilot study also reveals the impacts of transportation policies on the environment. To achieve a sustainable transportation system, the extent of the relationships between transportation and the environment must be considered. The World Development Indicators developed by the World Bank are used for this purpose

    Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model

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    The key role of technological change in the decline of energy and carbon intensities of aggregate economic activities is widely recognized. This has focused attention on the issue of developing endogenous models for the evolution of technological change. With a few exceptions this is done using a deterministic framework, even though technological change is a dynamic process which is uncertain by nature. Indeed, the two main vectors through which technological change may be conceptualized, learning through R&D investments and learning-by-doing, both evolve and cumulate in a stochastic manner. How misleading are climate strategies designed without accounting for such uncertainty? The main idea underlying the present piece of research is to assess and discuss the effect of endogenizing this uncertainty on optimal R&D investment trajectories and carbon emission abatement strategies. In order to do so, we use an implicit stochastic programming version of the FEEM-RICE model, first described in Bosetti, Carraro and Galeotti, (2005). The comparative advantage of taking a stochastic programming approach is estimated using as benchmarks the expected-value approach and the worst-case scenario approach. It appears that, accounting for uncertainty and irreversibility would affect both the optimal level of investment in R&D –which should be higher– and emission reductions –which should be contained in the early periods. Indeed, waiting and investing in R&D appears to be the most cost-effective hedging strategy.Stochastic Programming, Uncertainty and Learning, Endogenous Technical Change

    Teaching Construction in the Virtual University: the WINDS project

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    This paper introduces some of the Information Technology solutions adopted in Web based INtelligent Design Support (WINDS) to support education in A/E/C design. The WINDS project WINDS is an EC-funded project in the 5th Framework, Information Society Technologies programme, Flexible University key action. WINDS is divided into two actions: ·The research technology action is going to implement a learning environment integrating an intelligent tutoring system, a computer instruction management system and a set of co-operative supporting tools. ·The development action is going to build a large knowledge base supporting Architecture and Civil Engineering Design Courses and to experiment a comprehensive Virtual School of Architecture and Engineering Design. During the third year of the project, more than 400 students all over Europe will attend the Virtual School. During the next three years the WINDS project will span a total effort of about 150 man-years from 28 partners of 10 European countries. The missions of the WINDS project are: Advanced Methodologies in Design Education. WINDS drives a breakdown with conventional models in design education, i.e. classroom or distance education. WINDS implements a problem oriented knowledge transfer methodology following Roger Schank's Goal Based Scenario (GBS) pedagogical methodology. GBS encourages the learning of both skills and cases, and fosters creative problem solving. Multidisciplinary Design Education. Design requires creative synthesis and open-end problem definition at the intersection of several disciplines. WINDS experiments a valuable integration of multidisciplinary design knowledge and expertise to produce a high level standard of education. Innovative Representation, Delivery and Access to Construction Education. WINDS delivers individual education customisation by allowing the learner access through the Internet to a wide range of on-line courses and structured learning objects by means of personally tailored learning strategies. WINDS promotes the 3W paradigm: learn What you need, Where you want, When you require. Construction Practice. Construction industry is a repository of ""best practices"" and knowledge that the WINDS will profit. WINDS system benefits the ISO10303 and IFC standards to acquire knowledge of the construction process directly in digital format. On the other hand, WINDS reengineers the knowledge in up-to-date courses, educational services, which the industries can use to provide just-in-time rather than in-advance learning. WINDS IT Solutions The missions of the WINDS project state many challenging requirements both in knowledge and system architecture. Many of the solutions adopted in these fields are innovative; others are evolution of existing technologies. This paper focuses on the integration of this set of state-of-the-art technologies in an advanced and functionally sound Computer Aided Instruction system for A/E/C Design. In particular the paper deals with the following aspects: Standard Learning Technology Architecture The WINDS system relies on the in progress IEEE 1484.1 Learning Technology Standard Architecture. According to this standard the system consists of two data stores, the Knowledge Library and the Record Database, and four process: System Coach, Delivery, Evaluation and the Learner. WINDS implements the Knowledge Library into a three-tier architecture: 1.Learning Objects: ·Learning Units are collections of text and multimedia data. ·Models are represented in either IFC or STEP formats. ·Cases are sets of Learning Units and Models. Cases are noteworthy stories, which describes solutions, integrate technical detail, contain relevant design failures etc. 2.Indexes refer to the process in which the identification of relevant topics in design cases and learning units takes place. Indexing process creates structures of Learning Objects for course management, profile planning procedures and reasoning processes. 3.Courses are taxonomies of either Learning Units or a design task and Course Units. Knowledge Representation WINDS demonstrates that it is possible and valuable to integrate a widespread design expertise so that it can be effectively used to produce a high level standard of education. To this aim WINDS gathers area knowledge, design skills and expertise under the umbrellas of common knowledge representation structures and unambiguous semantics. Cases are one of the most valuable means for the representation of design expertise. A Case is a set of Learning Units and Product Models. Cases are noteworthy stories, which describe solutions, integrate technical details, contain relevant design failures, etc. Knowledge Integration Indexes are a medium among different kind of knowledge: they implement networks for navigation and access to disparate documents: HTML, video, images, CAD and product models (STEP or IFC). Concept indexes link learning topics to learning objects and group them into competencies. Index relationships are the base of the WINDS reasoning processes, and provide the foundation for system coaching functions, which proactively suggest strategies, solutions, examples and avoids students' design deadlock. Knowledge Distribution To support the data stores and the process among the partners in 10 countries efficiently, WINDS implements an object oriented client/server as COM objects. Behind the DCOM components there is the Dynamic Kernel, which dynamically embodies and maintains data stores and process. Components of the Knowledge Library can reside on several servers across the Internet. This provides for distributed transactions, e.g. a change in one Learning Object affects the Knowledge Library spread across several servers in different countries. Learning objects implemented as COM objects can wrap ownership data. Clear and univocal definition of ownerships rights enables Universities, in collaboration with telecommunication and publisher companies, to act as "education brokers". Brokerage in education and training is an innovative paradigm to provide just-in-time and personally customised value added learning knowledg

    Dealing with abstraction: Case study generalisation as a method for eliciting design patterns

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    Developing a pattern language is a non-trivial problem. A critical requirement is a method to support pattern writers with abstraction, so as they can produce generalised patterns. In this paper, we address this issue by developing a structured process of generalisation. It is important that this process is initiated through engaging participants in identifying initial patterns, i.e. directly dealing with the 'cold-start' problem. We have found that short case study descriptions provide a productive 'way into' the process for participants. We reflect on a 1-year interdisciplinary pan-European research project involving the development of almost 30 cases and over 150 patterns. We provide example cases, detailing the process by which their associated patterns emerged. This was based on a foundation for generalisation from cases with common attributes. We discuss the merits of this approach and its implications for pattern development
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