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The purpose of this paper is to shed further light on international financial linkages created by banks. Typically, the larger the balance sheet exposure a bank has to a counterparty country, the more will be both its risk exposure and sensibility to shocks to this latter. The latest crisis has revealed the importance of filling the existing data gaps which hinder a full understanding of the geographical composition of banks’ balance sheet on a global basis.

This paper, by focusing on US banks, reviews existing data on bilateral foreign positions on both a consolidated and an unconsolidated basis.

The investigation stresses the extent to which new data enhancements are going to enable to a better understanding of the global banking system and discusses other data limitations and gaps which should be addressed. In particular, policy recommendations point to the need to collect more detailed foreign offices-related statistics.

This is the first attempt in the literature to discuss data availability, limitations and policy suggestions regarding international bilateral banking statistics in the USA.

Hydrological and climatological modeling is increasingly being used with the intent of supporting community-based climate change adaptation (CCA) and disaster risk reduction (DRR) initiatives in the Hindu Kush-Himalaya (HKH), as well as filling critical data gaps in a region that contributes significantly to the water resources and ecosystem diversity of Asia. As the case studies presented in the previous chapters illustrate, the utility of modeling in informing and supporting CCA and DRR initiatives depends on a number of criteria, including:•appropriate model selection;•ability to interpret models to local contexts; and•community engagement that incorporates and addresses underlying vulnerabilities within the community.

There are significant challenges to meeting all three of these criteria. However, when these criteria are met, we find:•There is a clear role for modeling to support CCA. The climate is changing now and will continue to do so for several centuries, even if carbon emissions were to stabilize tomorrow. Models, and other scenario development tools, provide our best insight into what the future climate might be and resulting impacts on dynamic social, environmental, political, and economic systems.•There is a clear role for local CCA. The impacts of climate change will be felt mostly at local levels, necessitating community adaptation responses. At the same time, most of the HKH communities and countries engaged in CCA initiatives have pressing, immediate development and livelihood needs. Making current development and livelihood initiatives incorporate climate adaptation considerations is the best way to ensure that the choices made today can set us on paths of increasing resilience, rather than almost inevitable disaster, for the future.•To achieve the best of both modeling and CCA requires thoughtful and patient application of modeling, tailored to local needs, conditions, and politics, with communities engaged around all stages of generating, interpreting, and applying the results. This requires a rare combination of technical skill, cultural sensitivity, political awareness, and above all, the time to continually engage with and build relationships within the community in order to foster resilient change.

The purpose of this paper is to investigate the data profile of manufacturing small and medium enterprises (SMEs) with specific emphasis on understanding the data readiness of SMEs for discrete event simulation (DES) modelling.

Research was conducted through a review of literature and a survey research strategy of manufacturing SMEs.

This paper illustrates the data profile of manufacturing SMEs. Insight is provided on the types of data collected by SMEs, the collection methods used and how these data are stored by the SMEs. Additionally size and age effects are considered. Based on this data profile, conclusions are made regarding an indication of data readiness of manufacturing SMEs for DES modelling.

This research is focused specifically on manufacturing SMEs in Ireland, other countries and sectors are not investigated.

This paper provides owner-managers and senior management insight into the data profile of manufacturing SMEs and their potential for utilisation of DES for performance improvement and decision support.

This paper addresses the gaps that exist in the knowledge of the data profile of manufacturing SMEs and consequently the status of this profile with regard to the readiness of SMEs for DES modelling.

In the field of heritage science, especially applied to buildings and artefacts made by organic hygroscopic materials, analyzing the microclimate has always been of extreme importance. In particular, in many cases, the knowledge of the outdoor/indoor microclimate may support the decision process in conservation and preservation matters of historic buildings. This knowledge is often gained by implementing long and time-consuming monitoring campaigns that allow collecting atmospheric and climatic data.

Sometimes the collected time series may be corrupted, incomplete and/or subjected to the sensors' errors because of the remoteness of the historic building location, the natural aging of the sensor or the lack of a continuous check of the data downloading process. For this reason, in this work, an innovative approach about reconstructing the indoor microclimate into heritage buildings, just knowing the outdoor one, is proposed. This methodology is based on using machine learning tools known as variational auto encoders (VAEs), that are able to reconstruct time series and/or to fill data gaps.

The proposed approach is implemented using data collected in Ringebu Stave Church, a Norwegian medieval wooden heritage building. Reconstructing a realistic time series, for the vast majority of the year period, of the natural internal climate of the Church has been successfully implemented.

The novelty of this work is discussed in the framework of the existing literature. The work explores the potentials of machine learning tools compared to traditional ones, providing a method that is able to reliably fill missing data in time series.

This article introduces the Special Issue on Sustainable Management of Heritage Buildings in long-term perspective.

It starts by reviewing the gaps in knowledge and practice which led to the creation and implementation of the research project SyMBoL—Sustainable Management of Heritage Buildings in long-term perspective funded by the Norwegian Research Council over the 2018–2022 period. The SyMBoL project is the motivation at the base of this special issue.

The editorial paper briefly presents the main outcomes of SyMBoL. It then reviews the contributions to the Special Issue, focussing on the connection or differentiation with SyMBoL and on multidisciplinary findings that address some of the initial referred gaps.

The article shortly summarizes topics related to sustainable preservation of heritage buildings in time of reduced resources, energy crisis and impacts of natural hazards and global warming. Finally, it highlights future research directions targeted to overcome, or partially mitigate, the above-mentioned challenges, for example, taking advantage of no sestructive techniques interoperability, heritage building information modelling and digital twin models, and machine learning and risk assessment algorithms.

The purpose of this research is to establish that data on chemicals detected in the environment are urgently needed to comply with the future environment and chemicals policy in the European Union. The availability of data on chemicals can be evaluated by environmetrical and chemometrical methods.

The Hasse Diagram Technique (HDT) which originated in discrete mathematics is applied in this paper. It is a multi‐criteria evaluation method which can be used to measure information quality and is therefore also applicable for decision making. The study evaluated 15 environmental and chemical free internet databases with respect to the existence of data on chemicals in these resources. Two test‐sets were used first, 12 high production volume chemicals and, second 12 pharmaceuticals which are proven to enter the environment in considerable concentrations.

The evaluation indicates a rather disturbing situation in the data availability on existing chemicals, an especially bad result concerning the data availability on pharmaceuticals and hence an alarming signal concerning the chemicals policy of the EEC.

The information gap, especially for pharmaceuticals entering the environment, is demonstrated with a mathematically recognised method. The Hasse Diagram Technique can be applied to different questions in science when several objects are to be ranked by several criteria at the same time. Concerning the topic of the data availability on chemicals, the gaps are identified and should inspire future research to generate new and valuable data.

Mountains provide more than 40% of global goods and services. The ecosystem services arising from the Hindu Kush-Himalayas (HKH) in the form of water, biodiversity and niche products, hydroelectricity, timber, mineral resources, and recreation are enormous. The HKH region is enriched by a diversity of cultures, ethnic groups, and traditional knowledge systems. Thus, it is a paradox that, in spite of rich natural resources and cultures, poverty is rampant. Additionally, the HKH is a hotspot for climate change impacts, but the region has been identified as a data deficient during the 2007 assessment report of the Intergovernmental Panel on Climate Change (IPCC). Since then, some progress has been made to fill the data gap, specifically relating to biodiversity, cryosphere, and climate change. This chapter introduces the HKH region and elaborates the need for modeling in the context of dealing with climate change.

This research seeks to explain how a national government becomes capable of constructing an account of its biodiversity performance that is aimed at enabling formulation of policy in pursuit of SDG 15: Life on Land.

The research examines a case study of the construction of the UK government's annual biodiversity report. The case is analysed to explain the process of framing a space in which the SDG-15 challenge of halting biodiversity loss is rendered calculable, such that the government can see and understand its own performance in relation to this challenge.

The construction of UK government's annual biodiversity report relies upon data collected through non-governmental conservation efforts, statistical expertise of a small project group within the government and a governmental structure that drives ongoing evolution of the indicators as actors strive to make these useful for policy formulation.

The analysis problematises the SDG approach to accounting for sustainable development, whereby performance indicators have been centrally agreed and universally imposed upon all signatory governments. The analysis suggests that capacity-building efforts for national governments may need to be broader than that envisaged by the 2030 Agenda for Sustainable Development.

Across societies, gendered climate response decisions remain top-down and have limited progress because the influenced risk dynamics and their interrelations are not adequately understood. This study aims to address this gap by proposing an interdisciplinary innovative method, called women climate vulnerability (WCV) index, for measuring and comparing a diverse range of risks that threaten to undermine the adaptive capacity and resilience of rural women.

This paper builds on the literature to identify 12 risk categories across physical, economic and political sectors that affect rural women. These categories and attendant 51 risk indicators form the WCV index. A case study in Ben Tre Province (Vietnam) was used to demonstrate the application of the WCV methodology to rural contexts. The authors combined empirical, survey and secondary data from different sources to form data on the indicators. Structured expert judgment was used to address data gaps. Empirical and expert data were combined using a few weighting steps and a comprehensive coding system was developed to ensure objective evaluation.

The WCV assessment results reveal a reasonably worrisome picture of women’s vulnerability in Ben Tre as top highest-likelihood and deepest-impact risks predominate in physical and economic risk sectors. Stability, human security and governance categories have lowest scores, demonstrating a fairly politically favourable condition in the province. The medium risk scores captured in land and infrastructure categories reveal promising determinants of the adaptation of women in this rural province. The results demonstrate the usefulness of the WCV index in collecting bottom-up data, evaluating a wide variety of risks that rural women face and pinpointing priority areas that need to be addressed.

The WCV is systematic, customisable and localised. It combines field research and empirical data through structured expert judgment, thus enables researchers to fill data gaps and to do evidence-based assessment about diverse risk vulnerabilities. By doing so, the WCV index gives critical insights into the challenges that rural women face. This enables local governments to better understand cross-sectoral risks, pinpoint priority areas of action and timely channel funding and policy resources to support women where they need it most.

This paper aims to examine the Canadian financial sector’s reaction to opportunities and risks created by the green bond market in a low-carbon and climate-resilient (LCR) economy.

The authors used a concurrent mixed methodological approach that undertakes an online survey and semistructured interviews with critical green bond market stakeholders.

The most significant market driver in Canada is the reputational benefit for stakeholders, i.e. its ability to meet the high demand for sustainable finance and the marketing potential of its green credentials. The major market barriers are transactional costs, i.e. additional tracking required for reporting purposes, lack of market liquidity and identification of environmental impact or additionality. Canadian green bonds are also more likely to be evaluated on their green impact than their global market peers.

Limitations of this study include its focus on Canada, which may exclude or not apply to drivers and barriers in other green bond markets.

The paper helps create an accounting-based conceptual framework for key motivations and barriers that affect financial decision-making regarding green bonds.

The authors identify economic and policy-related barriers and drivers for green bonds, addressing the financing gap for the LCR economy.

To the best of the authors’ knowledge, this study is the first to identify and compare Canadian green bond market drivers and barriers and to examine relevant stakeholder- and policy-related approaches that can be targeted to scale this market effectively.