Reconstructing nonparametric productivity networks

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes. We fill this gap by developing a general framework to infer the network structure in a Bayesian sense, in order to better understand the underlying relationships driving system performance. Our approach draws on recent advances in information science, machine learning and statistical inference from the physics of complex systems to estimate unobserved network linkages. To illustrate, we apply our framework to analyze the production of knowledge, via own and cross-disciplinary research, for a world-country panel of bibliometric data. We find significant interactions between related disciplinary research output, both in terms of quantity and quality. In the context of research productivity, our results on cross-disciplinary linkages could be used to better target research funding across disciplines and institutions. More generally, our framework for inferring the underlying network production technology could be applied to both public and private settings which entail spillovers, including intra-and inter-firm managerial decisions and public agency coordination. This framework also provides a systematic approach to model selection when the underlying network structure is unknown

Negotiating the 'trading zone'. Creating a shared information infrastructure in the Dutch public safety sector

Our main concern in this article is whether nation-wide information technology (IT) infrastructures or systems in emergency response and disaster management are the solution to the communication problems the safety sector suffers from. It has been argued that implementing nation-wide IT systems will help to create shared cognition and situational awareness among relief workers. We put this claim to the test by presenting a case study on the introduction of ‘netcentric work’, an IT system-based platform aiming at the creation of situational awareness for professionals in the safety sector in the Netherlands. The outcome of our research is that the negotiation with relevant stakeholders by the Dutch government has lead to the emergence of several fragmented IT systems. It becomes clear that a top-down implementation strategy for a single nation-wide information system will fail because of the fragmentation of the Dutch safety sector it is supposed to be a solution to. As the US safety sector is at least as fragmented as its Dutch counterpart, this may serve as a caveat for the introduction of similar IT systems in the US

CAPRi technical workshop on Watershed Management Institutions: a summary paper

The System-wide Program for Collective Action and Property Rights (CAPRi) sponsored a workshop on Watershed Management Institutions, March 13-16, 1999 in Managua, Nicaragua. The workshop focused on methodologies for undertaking research on watersheds, particularly those issues and tools that enable a more thorough understanding of the complex interactions between the biophysical factors and socioeconomic institutions of watersheds. Both social and biophysical scientists from CGIAR and other research institutions were brought together to present research and participate in focused discussions on methodologies for addressing collective action and property rights, scale, participation, and impact assessment. The forum also provided an opportunity for participants to visit and learn from a watershed project being implemented by the International Center for Tropical Agriculture (CIAT), and to discuss one another's ongoing watershed research project experience and explore opportunities for collaboration.International Food Policy Research Institute (IFPRI), International Center for Tropical Agriculture (CIAT), Impact assessment,

The scientific impact derived From the disciplinary profiles

The disciplinary profiles of the mean citation rates across 22 research areas were analyzed for 107 countries/territories that published at least 3,000 papers that exceeded the entrance thresholds for the Essential Science Indicators (ESI; Clarivate Analytics) during the period from January 1, 2009 to December 31, 2019. The matrix of pairwise differences between any two profiles was analyzed with a non-metric multidimensional scaling (MDS) algorithm, which recovered a two-dimensional geometric space describing these differences. These two dimensions, Dim1 and Dim2, described 5,671 pairwise differences between countries' disciplinary profiles with a sufficient accuracy (stress = 0.098). A significant correlation (r = 0.81, N = 107, p < 0.0001) was found between Dim1 and the Indicator of a Nation's Scientific Impact (INSI), which was computed as a composite of the average and the top citation rates. The scientific impact ranking of countries derived from the pairwise differences between disciplinary profiles seems to be more accurate and realistic compared with more traditional citation indices

Actors and factors - bridging social science findings and urban land use change modeling

Recent uneven land use dynamics in urban areas resulting from demographic change, economic pressure and the cities’ mutual competition in a globalising world challenge both scientists and practitioners, among them social scientists, modellers and spatial planners. Processes of growth and decline specifically affect the urban environment, the requirements of the residents on social and natural resources. Social and environmental research is interested in a better understanding and ways of explaining the interactions between society and landscape in urban areas. And it is also needed for making life in cities attractive, secure and affordable within or despite of uneven dynamics.\ud The position paper upon “Actors and factors – bridging social science findings and urban land use change modeling” presents approaches and ideas on how social science findings on the interaction of the social system (actors) and the land use (factors) are taken up and formalised using modelling and gaming techniques. It should be understood as a first sketch compiling major challenges and proposing exemplary solutions in the field of interest

Worldwide bilateral geopolitical interactions network inferred from national disciplinary profiles

A disciplinary profile of a country is defined as the versor whose components are the number of papers produced in a given discipline divided by the overall production of the country. Starting from the Essential Science Indicators (ESI) schema of classification of subject areas, we obtained the yearly disciplinary profiles of a worldwide graph, where on each node sits a country, in the two time intervals 1988-1988 and 1992-2017, the fall of the Berlin Wall being the watershed. We analyze the empirical pairwise cross-correlation matrices of the time series of disciplinary profiles. The contrast with random matrix theory proves that, beyond measurement noise, the empirical cross-correlation matrices bring genuine information. Arising from the Shannon theorem as the least-structured model consistent with the measured pairwise correlations, the stationary probability distribution of disciplinary profiles can be described by a Boltzmann distribution related to a generalized n(d)-dimensional Heisenberg model. The set of network interactions of the Heisenberg model has been inferred and to it, two clusterization methods, hierarchical clustering, and principal component analysis have been applied. This allows obtaining a characterization of the worldwide bilateral interactions based on physical modeling. A simple geopolitical analysis reveals the consistency of the results obtained and gives a boost to a deeper historical analysis. In order to obtain the optimal set of pairwise interactions, we used a pseudolikelihood approach. We analytically computed the pseudolikelihood and its gradient. The analytical computations deserve interest in whatever inference Bayesian problem involving an n(d)-dimensional Heisenberg model

Advances in risk assessment for climate change adaptation policy

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordClimate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’.The authors acknowledge support from the UK Department for Environment, Food and Rural Affairs in the preparation of the International Dimensions Assessment of the UK Climate Change Risk Assessment. W.N.A. acknowledges support from High-end Climate Impacts and Extremes project of the EU. S.S. would like to acknowledge the financial support of Ireland’s Environmental Protection Agency (EPA) under the EPA Research Programme 2014–2020, of the UK Economic and Social Research Council (ESRC) through the Centre for Climate Change Economics and Policy, and of the Grantham Foundation for the Protection of the Environment through the Grantham Research Institute on Climate Change and the Environment