Support Policy Decisions Research Articles

The Economics of Consensus in Algorand

In the paper we investigate consensus formation, from an economic perspective, in a Proof-of-Stake (PoS) based platform inspired by the Algorand blockchain. In particular, we consider PoS in relation to governance, focusing on two main issues. First we discuss alternative sampling schemes, which can be adopted to select voting committees and to define the number of votes of committee members. The selection probability is proportional to one’s stake and increases with it. Participation in governance allows users to affect the platform’s decisions as well as to obtain a reward. Then, based on such preliminary analysis, we introduce a microeconomic model to investigate the optimal stake size for a generic user. In the model we conceptualize an optimal stake, for a user, as striking the balance between having Algos immediately available for transactions and setting aside currency units to increase the probability of becoming a committee member. Our main findings suggest that the optimal stake can be quite sensitive to the user’s preferences and to the rules for selecting committees. We believe the findings may support policy decisions in PoS based platforms.

Pragmatic Validation of Numerical Models Used for the Assessment of Radioactive Waste Repositories: A Perspective

The safety case for a radioactive waste repository relies heavily on results obtained by numerical models that assess the long-term performance of the engineered and natural barrier systems. Given that important engineering and public policy decisions are based on these models, it is essential that we critically evaluate their abilities and limitations, and thus justify the level of confidence we have in the inferences drawn from the modeling. In this article, we discuss some of the issues surrounding the modeler’s attempts to test, corroborate, confirm, and verify numerical models—a process sometimes referred to as model validation. This wide-ranging topic is approached by first examining its deep roots in the philosophy of science and hypothesis testing. However, the application of these principles to radioactive waste isolation calls for a more pragmatic approach, which has the narrower goal of corroborating site-specific models and their usefulness for a specific purpose. We focus on the practical aspects of validating hydrogeological models that are used to understand the evolution of the repository system. We will make the case that the responsible use of numerical models requires a sufficient understanding of the quality and robustness of the simulation results, with direct implications for how these results need to be interpreted, and how they can (or cannot) be used in support of important policy decisions.

Biological invasions reveal how niche change affects the transferability of species distribution models.

Species distribution models (SDMs) have been widely applied to predict geographic ranges of species across space and time under the assumption of niche conservatism (i.e., species niches change very slowly). However, an increasing number of studies have reported evidence of rapid niche changes across space and time, which has sparked a widespread debate on whether SDMs can be transferred to new areas or time periods. Understanding how niche changes affect SDM transferability is thus crucial for the future application and improvement of SDMs. Biological invasions provide an opportunity to address this question due to the geographically independent distributions and diverse patterns of niche changes between species' native and introduced ranges. Here, we synthesized findings on 217 species from 50 studies to elucidate the effects of niche change on the spatial transferability of SDMs. When niche change was considered as a categorical classification (conserved vs. shifted niches) in tests of the niche conservatism hypothesis, SDM transferability was markedly lower for species with a shifted niche in their introduced range. When niche change was measured as numerical dynamics between native and introduced niches, SDM transferability was high for species occupying similar environmental conditions in both ranges and low for species with more environmental space remaining unoccupied in the introduced range. Surprisingly, the number of presence points used for developing SDMs turned out to have an even stronger effect on transferability. Our results thus reveal detrimental effects of both niche change and lack of presence points on SDM transferability. It is necessary to consider both niche change and data quality for improving the transferability of SDMs, so that they can better support conservation management and policy decisions.

What is required to combine human biomonitoring and health surveys?

Obtaining holistic information about health and health determinants at the population level should also include data on environmental risk factors of health. So far, only a few countries have combined, at the national level, health and human biomonitoring (HBM) surveys to collect extensive information on health, lifestyles, biological health determinants and environmental exposures. This paper will provide guidelines on how to combine health and HBM surveys and what is the added value of doing so. Health and HBM surveys utilize similar infrastructure and data collection methods including questionnaires, collection and analysis of biological samples, and objective health measurements. There are many overlapping or comparable steps in these two survey types. At the European level, detailed protocols for conducting a health examination survey or HBM study exists separately but there is no protocol for a combined survey available by now. Our recommendations for combined health and HBM surveys focus on a cross-sectional survey on general population aged 6-79 years. To avoid unnecessary participant burden, for the selection of included measurements basic principle would be to ensure that results of the measurements have a public health relevance and clear interpretation. Combining health and HBM surveys into one survey would produce an extensive database for research to support policy decisions in many fields such as public health and chemical regulations. Combined surveys are cost-effective as only one infrastructure is needed to collect information and recruit participants.

Improving neural network classification of indigenous forest in New Zealand with phenological features

Accurate and up-to-date land cover maps inform and support effective management and policy decisions. Describing phenological changes in spectral response using time-series data may help to distinguish vegetation types, thereby allowing for more specificity within vegetation classification. In this research, we test this by classifying indigenous forest vegetation in New Zealand, using PlanetScope (PS) and Sentinel-2 (S-2) satellite time-series data.The study was undertaken in a podocarp forest in New Zealand's central north island, which was classified into nine land cover classes. Phenological features, based on S-2 imagery, were extracted, including the enhanced vegetation index (EVI), enhanced vegetation index 2 (EVI2) and normalised difference vegetation index (NDVI). Google Earth Engine (GEE) harmonic analysis and TIMESAT double logistic fitting function were used to extract phenological features. Pixel-based classifications were performed using a Neural Network on six different scenarios. The accuracy of the classification scenarios was determined and the importance score for each feature was evaluated.Using only the fused PS and S-2 bands, the land cover in the study area was classified with 90.1% accuracy. Adding phenological features increased the classification accuracy to 93.1%. When combined with VIs, texture features, and a digital terrain model, the addition of phenological features increased the classification accuracy to 96.6%. Including GEE-generated phenological features resulted in better classification accuracies than TIMESAT features. In terms of feature importance evaluation, EVI2- and NDVI-generated phenological features all had high scores; the effectiveness of EVI features could potentially have been limited by the quality of the blue band. The results demonstrate that it is possible to produce a more accurate classification of New Zealand's native vegetation by using phenological features. This method offers important cost-savings as the platforms for phenological analysis are free to use.

Long-term design and analysis of renewable fuel supply chains – An integrated approach considering seasonal resource availability

Replacing fossil fuels by renewable liquid fuels produced from electricity, biomass, and carbon dioxide can substantially reduce emissions in the transport sector. A multitude of planning tasks arise as the widespread use of renewable fuels requires extensive investments in renewable electricity generation, fuel production plants, storage facilities, and pipeline-based transport infrastructures. Hence, we develop a mathematical model determining the optimal design and operation of renewable fuel supply chains to support policy decisions for the transport sector. Strategic decisions include multi-period locational decisions on installing wind and solar generation capacities and investment in fuel production plants, storage capacities, and pipeline-based transport infrastructure. Tactical decisions include production, transport, and storage quantities along with the annual seasonal utilization of resources. Our mathematical formulation is able to consider various resource origins as well as production, transport, and storage processes. To reduce the number of consecutive time periods, we divide the planning horizon into strategic and tactical decision levels connected by a cyclic storage formulation. We apply the model to a European case study to support policy makers with insights into advantageous designs of transnational fuel supply chains to enable a climate-neutral European transport sector. Furthermore, we provide additional scenario analyses regarding the maximum installable capacity for renewable electricity generation as well as biomass and carbon dioxide availability, and fuel demand development.

Access of Technology as a Mediator on Access to Finance to Drive Business Innovation in Small to Medium-Sized Enterprises

Abstract This study assesses the role played by access to finance as an indirect stimulant of business development and economic growth. The ‘access to technology is considered as a mediator in analyzing growth. A dataset that spans five years was gathered from small to medium-sized enterprises (SMEs) in different sectors, was analyzed as panel data through fixed and random effect regression estimation models. The results showed that access to technology playing marked role in mediating the relationship between access to finance and the adopted process sophistication. The results further showed that while access to finance is crucial driver for development in emerging economies, the access to technology seem to play more active role through stimulated growth owing to incremental improvements in business process sophistication. This study finds that multiple factors stemming from a firm’s access and use of newer forms of technology can play an essential role in generating these results, in particular the more straightforward access to finance. These findings were analyzed and interpreted under conditions that control for standard macroeconomic economic growth factors. The conclusions support policy decisions of governmental agencies that aim to improve financial support services and facilitate ease of access to cutting edge technologies.

IDF21-0168 Pathway to Clinical Diabetes Services in COVID-19 Era: What Has Changed and What Are the Implications?

Background: The known barriers to delivering clinical NCD services in lower-middle-income countries (LMICs) have been exacerbated with the onset of COVID-19. Health facility-instituted COVID-19 control measures could compromise the pathway for seeking care and impact chronic disease care that needs to be examined for future policy direction. Aim: This paper examines the changes COVID-19 has brought to diabetes service delivery in LMICs, using Ghana as a case study, and raises questions on the implication of such changes on the individual- and population-level diabetes treatment outcomes by exploring service provider perspectives. Ghana first recorded COVID-19 cases in March 2020, and from April, the government started implementing lockdown measures as well as closing hospitals' outpatient services, including diabetes clinics and other NCDs services. Method: We conducted eighteen semi-structured personal interviews with healthcare providers in primary, secondary and tertiary facilities within the Ghana Health Service. The topic guide was developed from a literature review conducted for this study and addressed issues such as COVID-19 and service organisation, staffing, referrals, patient concerns, data management and insurance. The interviews were conducted between November 2020 and February 2021, when outpatient services, including diabetes clinics, resumed operations. The analysis was performed using inductive and deductive methods in NVivo 1.4.1. Results and Discussion: The study found that suboptimal patient appointments and reminder systems result in overcrowded diabetes clinics, further increasing the risk of COVID-19 epidemic in hospitals. Tackling overcrowded diabetes clinics is urgently needed with the potential for patients and providers becoming infected with COVID-19. Engineering controls, e.g. fans instead of air conditioners to improve air circulation and ventilation, can help minimize transmission in hospital buildings. COVID-19 controls, e.g., extended time intervals between reviews, fewer appointments per clinic day, and shorter consultation durations, limit opportunities for clinicians to intervene in patients' conditions and consequently lead to poor treatment outcomes. Health systems need to investigate the cost-effectiveness of such controls to support policy decisions. National health insurance and drug policies limit health facilities and diabetes patients access to medicines in the COVID-19 era. Restrictions on the procurement and sales of insured medicines to patients contributed to the shortage of diabetes medication. Granted permission to procure medicines on the open market, a limit on the profit margin to put on medicine cost can result in a loss for health facilities. Known diabetes service delivery challenges, e.g. few trained providers, high treatment cost, and drug shortage, were aggravated, particularly in ambulatory care, during the pandemic. The UK and Italy adapted Facebook chatting, video tele-consultation and government websites for delivering diabetes care during the COVID-19 pandemic. However, we are aware that resource constraints may limit the implementation of similar strategies in LMICs. Our study suggests that COVID-19 presents additional challenges and worsens existing barriers to diabetes service delivery for clinicians and people living with diabetes. These challenges could have negative implications for population-level diabetes treatment outcome, interfering with the sustainable development goals. Further research remains to assess the effect of COVID-19-related structural changes on treatment adherence and outcomes in practice.

How far are we from possible ideal virtual water transfer? Evidence from assessing vulnerability of global virtual water trade

With the increasing contradiction between water demand and supply in a telecoupled society where nature and human interplay intensively over distance, virtual water trade (VWT) plays an indispensable role in global water use sustainability. There has been little quantitative analysis of global water use sustainability depicting both overall system characteristics and flows between subsystems. In such a context, the extent to which virtual water transfer deviates from possible ideal expectations (i.e., virtual water flows from water-abundant regions to water-scarce ones), and its impact on global water use sustainability, are not well evaluated. Therefore, the global VWT vulnerability framework is proposed to delineate the gap between the real VWT and the possible optimal scenario, providing potential space for future optimization and regulation. Represented by the ratio of weighted total virtual water volume to the original one, the vulnerability is assessed from 2005 to 2015 based on the Eora input-output database and Virtual Water Transfer Multiplier which assigns differentiated weights to per unit volume of virtual water transfer based on the water stress levels of importers and those of exporters. Results show that the global VWT vulnerability has increased by 18.9% during the study period, with Africa and Southern and Central Asia making the biggest contribution. Developed countries contributed around 80% of the increased global VWT vulnerability. However, the proportion has fallen a bit, in terms of the conventional view of developed countries taking the approach of transferring responsibility to developing countries. Instead, the proportions of transferring responsibility between developing countries have rose by 10% to 30% during 2005–2015, partially due to stronger trade ties among developing countries. Our findings support policy decisions on tracing environmental responsibility for water scarcity and call for action to prevent water ecological downsides due to international trade.

Political nonprofits and dark money in Alabama education politics

The proliferation of political nonprofit organizations since the Citizens United decision has undoubtedly reshaped American politics. These interest groups have spent hundreds of millions of dollars in recent state and federal elections. Yet, little is known about how these organizations influence higher education politics and the extent to which higher education leaders rely on political nonprofits to increase state support and tilt policy decisions in their favor. To that end, this descriptive case study analysis explores the purpose and activities of a short-lived political nonprofit organization in Alabama, the Alabama Association for Higher Education (AAFHE). Using publicly available data, I developed a follow-the-money scheme to illustrate the activities of the AAFHE and its affiliates. Findings suggest that leaders of the University of Alabama System established the AAFHE to sustain and obtain resources through political contributions and lobbying at the state and federal levels. The AAFHE employed several direct and indirect lobbying strategies to secure state and federal resources for higher education institutions in Alabama, primarily those within the University of Alabama System. The study highlights the ethical and practical challenges campus leaders face when using political nonprofits to advance institutional goals.

Adoption of open innovation in the COVID-19 emergency: developing a process-based information coordination system

PurposeThe COVID-19 pandemic has stimulated a global movement of open innovation initiatives aimed to provide knowledge and tools to support policy decisions and actions in the emergency scenario. The authors describe an open innovation process aimed to build an information coordination system to reduce the infection diffusion within the population.Design/methodology/approachThe authors use coordination theory principles to elaborate a framework of activities, resources and dependencies among information resources and producers in the COVID-19 emergency. The framework was applied to develop a case study aimed at describing a health emergency system implemented by Dyrecta Lab (a research laboratory on computer science) and CITEL (a medical research center).FindingsThe authors describe the existence of relevant “flow,” “fit” and “share” dependencies within the activities of infection containment and medical treatment. The authors identify eight key resources and a number of actors involved in those activities, and describe a platform able to gather a multitude of epidemic-related metrics with the purpose to address dependencies and support decision making.Research limitations/implicationsThe authors provide insights for advancing the academic discussion on process coordination principles in time-constrained, volatile and highly demanding scenarios.Practical implicationsThe value of the authors’ research can be identified for practitioners engaged to develop innovative development projects for public utility. The authors provide a contribution also for first responders and health operators involved in management of the current and future emergencies.Originality/valueThe adoption of process coordination principles is a relatively new and powerful approach to analyze and optimize the processes that characterize the management of emergency scenarios. Besides, the study and application of open innovation in healthcare are partially limited.

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data

Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamics of hotspot events is of great importance to support policy decisions and prevent large-scale outbreaks. This paper presents a spatio-temporal Bayesian framework for early detection of COVID-19 hotspots (at the county level) in the United States. We assume both the observed number of cases and hotspots depend on a class of latent random variables, which encode the underlying spatio-temporal dynamics of the transmission of COVID-19. Such latent variables follow a zero-mean Gaussian process, whose covariance is specified by a non-stationary kernel function. The most salient feature of our kernel function is that deep neural networks are introduced to enhance the model's representative power while still enjoying the interpretability of the kernel. We derive a sparse model and fit the model using a variational learning strategy to circumvent the computational intractability for large data sets. Our model demonstrates better interpretability and superior hotspot-detection performance compared to other baseline methods.

State-level regulations and opioid-related health outcomes

IntroductionDue to the ongoing opioid use disorder crisis, improved access to opioid treatment programs (OTPs) is needed. However, OTPs operate in a complex regulatory environment which may limit their ability to positively affect health outcomes. The objective of this study was to examine how the number and type of state OTP regulations are associated with opioid-related deaths, hospitalizations, and emergency department visits. MethodsCross-sectional data capturing information about OTP state-level regulations collected by Jackson et al. was combined with other secondary sources. OTP regulations were categorized based on the nature of their focus. Analyses include bivariate and multivariable regressions that controlled for region and other state laws that can affect opioid outcomes. ResultsIn bivariate analysis, a greater number of OTP regulations was positively correlated with both deaths and emergency visits. Moreover, a greater number of regulations in the Physical Facilities Management category (e.g., rules related to restrooms, lighting, and signage) was positively correlated with both deaths and hospitalizations. The number of regulations in the Staffing Requirement category was positively associated with emergency visits. In adjusted analysis, the number of regulations in the Physical Facilities Management category was positively associated with opioid-related deaths. ConclusionsStates with a higher number of regulations had poorer opioid-related outcomes. Additional research is needed to support policy decisions that can improve access to OTPs and reduce avoidable deaths, hospitalizations, and emergency visits.

Политические парадоксы экономических санкций

The article addresses political economy aspects of the policy of economic sanctions. Given the fact that decisions taken both in sender and target countries depend on the interaction of numerous groups of political and economic agents, sanction research can be productive only if their behavior is explicitly modelled given their objective functions and institutional context they face. It is shown that political economy approach can help resolve a number of paradoxes common in sanction research, i. e., paradoxes related to ineffi ciency of sanctions, pro-conflict reaction on sanctions by target countries, escalation of inefficient sanctions by sender countries, and retaliatory measures. Analysis shows that escalation of economic sanctions against the Russian Federation can not shift country’s foreign policy in the direction preferred by sender countries. On the contrary, higher sanction costs for the Russian economy fuel domestic political support for current foreign policy decisions. Consequently, conflict resolution should rely upon multilateral political dialogue rather than economic sanctions.

Parachute science through a regional lens: Marine litter research in the Caribbean Small Island Developing States and the challenge of extra-regional research

The Wider Caribbean (WC) comprises numerous diverse developing states and territories including Small Island Developing States (SIDS). In particular, the Eastern part of the WC with its 16 SIDS receives a disproportionate amount of marine litter. Addressing this serious and urgent environmental problem requires scientific evidence to support and inform policy formation and decision making. Yet, as this study demonstrates, marine scientific research on the issue of marine litter in the Caribbean SIDS is predominantly undertaken by extra-regional scientists and organisations which might weaken the science-policy transfer to develop suitable and tailor-made solutions. The view point paper highlights issues and the problems associated with parachute science for the Caribbean SIDS before offering a series of potential policy-ready response options to address the identified challenges.

Benefits of policy actor embeddedness for sustainable tourism indicators’ design: the case of Andalusia

To ensure effective management, tourism governments need tools that can measure tourism activities’ impacts on sustainable development. Systems of indicators are thus widely used in tourism sustainability management and need to find a balance between academic and professional perspectives. This research is a case study focused on a tool for monitoring regional government policies: the Andalusia System of Sustainable Tourism Development Indicators (SISTA). The system was developed by an interdisciplinary group of 15 experts from within the regional government and academia. We apply the institutional theory in the tourism public sector to study a process of deinstitutionalization to get insights on how actors within tourism management organizations can shape institutions. Our results demonstrate that policy actors’ participation enhances these systems’ usefulness, introducing the sustainability policy paradigm and raising awareness of the strategic uses of data to support policy decisions. On the other hand, challenges of policy actors’ participation are related to the mismatch between sustainability evolution and policy cycles, and from the difficulty of judging policy measures’ efficiency. This research will serve as a reference for other tourism destinations working on measuring system development with practical applications as well as for academia to integrate policy actors’ needs into theoretical approaches.

Editorial: Using Ecological Models to Support and Shape Environmental Policy Decisions

Editorial: Using Ecological Models to Support and Shape Environmental Policy Decisions

Reevaluation of the carbon emissions embodied in global value chains based on an inter-country input-output model with multinational enterprises

Multinational enterprises actively participate in global production networks. However, the current global value chain accounting framework fails to consider the emissions originating from the production activities of multinational enterprises in the host country and may underestimate the carbon emissions embodied in global value chain activities. This paper proposed an Inter-Country Input-Output decomposition framework that can distinguish domestic firms and multinational enterprises and recalculated global value chain emissions including emissions embodied in international trade (trade-related GVC emissions), foreign direct investment (FDI-related GVC emissions), and both (trade and FDI related GVC emissions). We found that 1) the carbon emissions originating from global value chain activities were underestimated by about 13.8 percentage points under the original framework in 2016, and a large part was classified as emissions stemming from pure domestic production activities; 2) the FDI-related GVC emissions were notable in high-income economies and high-tech manufacturing sectors; 3) foreign direct investment mainly drove the emissions of upstream domestic firms through the joint domestic production linkage between domestic firms and multinational enterprises, especially in upper-middle-income countries; 4) from 2005 to 2016, the FDI-related GVC emissions increased by approximately 704.6 million tons, which was mainly attributed to the scale effect, whereas the carbon intensity effect caused a reduction. The results of this study exhibit a potential significance for the correct identification of the environmental impacts of global production fragmentation, and support policy decisions on national emission responsibilities and quotas determination, differentiated foreign investment decisions, and cleaner production development.

Accounting for Pandemic: Better Numbers for Management and Policy

AbstractInfection, hospitalization and mortality statistics have played a pivotal role in forming social attitudes and support for policy decisions about the 2020-21 SARS-CoV-2 (COVID-19) pandemic. This article raises some questions on some of the most widely-used indicators, such as the case fatality rate, derived from these statistics, recommending replacing them with information based on regular stratified statistical sampling, coupled with diagnostic assessment. Some implications for public health policies and pandemic management are developed, opposing individualistic and holistic approaches.

Estimating Destination of Bus Trips Considering Trip Type Characteristics

Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or policy decision support due to missing information on alighting stops of users. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. In order to overcome these limitations, various methods for estimating alighting stops have been developed. This study classifies trips with missing alighting stop information into trip four types and then applies appropriate alighting stop estimation methodology for each trip type in stages. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checking the accuracy for each standard of allowable error for sensitivity analysis. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can estimate users’ destinations more accurately than the methodologies of previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies.