Business models for climate services: An analysis

Climate services support mitigation and adaptation to climate change and encourage a science-based and climate-informed policy development. A performing market is vital for supporting uptake of climate services. The diffusion of innovations depends on how business models – meant as firms’ strategic choices to create, capture and share value within a value network – are employed. Innovation in business model, rather than product innovation only, has been proved useful for overcoming bottlenecks associated with development and diffusion of technologies. But only few studies have analysed how business models are used within the context of climate services. We fill this gap by using a sample of 32 climate services provisions at different stage of development. We use an original and revised version the Business Model Canvas as a framework to facilitate the data collection and analysis processes. A quali-quantitative approach is employed to tackle the content of the administered semi-structured interviews and to map them into a connected set of nodes representing concepts as provided by the selected informants. By combining Content and Network Analysis we present how business model aspects interact both within and across components. We find that the Value Network in which climate services operate is crucial for success, while a subscription, online-based infrastructure is a widespread tool in reaching the target users. The creation of partnerships and consortia of organisations allows mutual learning opportunities to happen and boosts the innovation behind these products. We focus on the graph giant component to highlight the role of co-creation approach in generating direct and indirect incremental innovations while delivering seasonal forecasts and tailor-made services. Finally, we call for tighter link between business and climate-related aspects to enhance the importance of financial considerations around climate services provision

Network Analysis, Creative System Modelling and Decision Support: The NetSyMoD Approach

This paper presents the NetSyMoD approach – where NetSyMod stands for Network Analysis – Creative System Modelling – Decision Support. It represents the outcome of several years of research at FEEM in the field of natural resources management, environmental evaluation and decision-making, within the Natural Resources Management Research Programme. NetSyMoD is a flexible and comprehensive methodological framework, which uses a suite of support tools, aimed at facilitating the involvement of stakeholders or experts in decision-making processes. The main phases envisaged for the process are: (i) the identification of relevant actors, (ii) the analysis of social networks, (iii) the creative system modelling and modelling of the reality being considered (i.e. the local socio-economic and environmental system), and (iv) the analysis of alternative options available for the management of the specific case (e.g. alternative projects, plans, strategies). The strategies for participation are necessarily context-dependent, and thus not all the NetSyMod phases may be needed in every application. Furthermore, the practical solutions for their implementation may significantly differ from one case to another, depending not only on the context, but also on the available resources (human and financial). The various applications of NetSyMoD have nonetheless in common the same approach for problem analysis and communication within a group of actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through the mDSS software.Social Network, Integrated Analysis, Participatory Modelling, Decision Support

Brief communication: Sendai framework for disaster risk reduction – success or warning sign for Paris?

In March 2015, a new international blueprint for disaster risk reduction (DRR) has been adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14–18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading to the Sendai Framework for DRR (SFDRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change

Environmental Policy Aid Under Uncertainty

Recent emphasis on uncertainty in environmental decision making reflects numerous changes in environmental science and policy making over the past few decades. Firstly, environmental policy problems increasingly involve large, interconnected and complex social choices. For example, climate change, ozone depletion, biodiversity loss, genetically-engineered crops, environment-related diseases and health risks involve large scale, long-term impacts, whose precise causes and consequences are often poorly understood. Given these uncertainties and the risk of irreversible environmental changes, different perspectives about the nature, policy implications, or even the existence of a problem, are inevitable (Rittel and Webber, 1973; Sarewitz, 2004)

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy

The Politics of (and Behind) the UNFCCC’s Loss and Damage Mechanism

Despite being one of the most controversial issues to be recently treated within climate negotiations, Loss and Damage (L&D) has attracted little attention among scholars of International Relations (IR). In this chapter we take the “structuralist paradox” in L&D negotiations as our starting point, considering how IR theories can help to explain the somewhat surprising capacity of weak parties to achieve results while negotiating with stronger parties. We adopt a multi-faceted notion of power, drawing from the neorealist, liberal and constructivist schools of thought, in order to explain how L&D milestones were reached. Our analysis shows that the IR discipline can greatly contribute to the debate, not only by enhancing understanding of the negotiation process and related outcomes but also by offering insights on how the issue could be fruitfully moved forward. In particular, we note the key importance that discursive power had in the attainment of L&D milestones: Framing L&D in ethical and legal terms appealed to standards relevant beyond the UNFCCC context, including basic moral norms linked to island states’ narratives of survival and the reference to international customary law. These broader standards are in principle recognised by both contending parties and this broader framing of L&D has helped to prove the need for action on L&D. However, we find that a change of narrative may be needed to avoid turning the issue into a win-lose negotiation game. Instead, a stronger emphasis on mutual gains through adaptation and action on L&D for both developed and developing countries is needed as well as clarity on the limits of these strategies. Examples of such mutual gains are more resilient global supply chains, reduction of climate-induced migration and enhanced security. As a result, acting on L&D would not feel as a unilateral concession developed countries make to vulnerable ones: it would rather be about elaborating patterns of collective action on an issue of common concern

Brief communication: Sendai framework for disaster risk reduction – success or warning sign for Paris?

In March 2015, a new international blueprint for disaster risk reduction (DRR) was adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14–18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading the Sendai Framework for DRR (SFDRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change

Testing empirical and synthetic flood damage models: The case of Italy

Flood risk management generally relies on economic assessments performed by using flood loss models of different complexity, ranging from simple univariable models to more complex multivariable models. The latter account for a large number of hazard, exposure and vulnerability factors, being potentially more robust when extensive input information is available. We collected a comprehensive data set related to three recent major flood events in northern Italy (Adda 2002, Bacchiglione 2010 and Secchia 2014), including flood hazard features (depth, velocity and duration), building characteristics (size, type, quality, economic value) and reported losses. The objective of this study is to compare the performances of expert-based and empirical (both uni- and multivariable) damage models for estimating the potential economic costs of flood events to residential buildings. The performances of four literature flood damage models of different natures and complexities are compared with those of univariable, bivariable and multivariable models trained and tested by using empirical records from Italy. The uni- and bivariable models are developed by using linear, logarithmic and square root regression, whereas multivariable models are based on two machine-learning techniques: random forest and artificial neural networks. Results provide important insights about the choice of the damage modelling approach for operational disaster risk management. Our findings suggest that multivariable models have better potential for producing reliable damage estimates when extensive ancillary data for flood event characterisation are available, while univariable models can be adequate if data are scarce. The analysis also highlights that expert-based synthetic models are likely better suited for transferability to other areas compared to empirically based flood damage models