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Infrastructure systems and facilities have deteriorated due to the impact of limited defense funding and competing priorities within the Air Force. The current method used for infrastructure prioritization is influenced by political sensitivity and uncertainty regarding the consequences of various funding decisions. Senior leaders need to better understand how their funding decisions will impact the overall condition and service life of the installation's infrastructure systems and facilities. The purpose of this research was to improve the method of prioritizing infrastructure projects through the use of a decision analysis methodology known as Value-Focused Thinking. The value model was created based on the perspective of the civil engineer with inputs from a proxy decision maker at Headquarters Air Force Materiel Command. The model was used to apply three funding strategies to develop prioritized lists of restoration and modernization projects. It also applies metrics to compare the three funding strategies and their impact to the installation's infrastructure. The resulting model provides insight to the decision maker on which funding strategy is best suited for prioritizing infrastructure projects and how their selection of prioritized projects will impact the overall condition and service life of infrastructure systems and facilities.

Disruption of infrastructure services can cause significant social and economic losses, particularly in the event of a natural disaster. The World Bank Group and the Government of Japan established the Quality Infrastructure Investment Partnership to focus attention on the quality dimensions of infrastructure in developing countries, with a focus on promoting disaster resilience. Moreover, to support infrastructure investment decision making for sustainable and resilient development, the World Bank and Kyoto University have operationalized key resilience concepts at the project level and developed quantitative indicators capturing key aspects of infrastructure resilience related to the road transport sector. These indicators estimate resilience, expressed as functionality loss and recovery time across four dimensions: travel time, economic benefit, provision of life-saving services, and provision of relief goods. The paper applies indicator calculations to three case studies of proposed bypass roads in Japan and provides an example comparison of calculated indicators across the three projects for each resilience dimension. Further piloting of the approach will help refine the indicators, test their relative utility in decision making, and offer a better understanding of the data and analytical demands.

Infrastructure services are significant determinants of economic development, social welfare, trade, and public health. As such, they typically feature strongly in national development plans. While governments may receive many infrastructure project proposals, however, resources are often insufficient to finance the full set of proposals in the short term. Leading up to 2020, an estimated US$836 billion - 1 trillion will be required each year to meet growth targets worldwide (Ruiz-Nunez and Wei, 2014; World Bank). Global estimates of infrastructure investments required to support economic growth and human development lie in the range of US$65-70 trillion by 2030 (OECD, 2006), while the estimated pool of available funds is limited to approximately US$45 trillion (B20, 2014). The past twenty years have also seen a shift towards decentralized infrastructure planning. Many subnational governments, regional entities, and sector agencies have been delegated responsibility for infrastructure planning promote local responsiveness, but responsibility for allocating funds often remains with a centralized finance agency (CFA). While constituencies may propose numerous projects, governments often have insufficient financial resources to implement the full suite of proposals. This report presents the IPF methodology and results of the pilot application to a select set of transport and water and sanitation projects in Panama. The report first gives background information on infrastructure prioritization in Panama, then follows with a description of the IPF in technical and implementation terms. Next, we present the results of the pilot and close with recommendations for implementing IPF to a wider set of projects.

Governments are challenged to balance multiple policy goals and make difficult choices when selecting infrastructure projects for public investment, particularly since available funds are often insufficient to implement the full suite of proposals. This paper presents the application of the Infrastructure Prioritization Framework, a systematic, multi-criteria approach to infrastructure project prioritization, to inform the selection of water supply investments in Sri Lanka. A set of 28 proposed water supply projects was prioritized at the request of the National Planning Department of Sri Lanka, based on consideration of multiple goals, including improved water quality and service, network extension, service provision to poor communities, job creation, and sound financial performance. This paper reviews the Infrastructure Prioritization Framework methodology; presents the results of the prioritization exercise, including an expanded sensitivity analysis; and discusses the way forward to apply the Infrastructure Prioritization Framework to inform infrastructure investment decisions.

AbstractWith coordinated military and civil operations in developing countries, the integration of local stakeholder values with the goals of security and nation building is crucial. Such integration encourages innovative and effective courses of action and prioritization of resources. Although tools of multi‐criteria decision analysis are well suited for resource prioritization, designing practical stakeholder value judgment elicitation in developing countries is a challenge because of cultural, organizational, and other barriers. Specifically, the weight of individual decision criteria can increase or decrease when diverse scenarios of emergent conditions are introduced or advocated by various stakeholders. This article develops methodology to identify the most important emergent conditions for infrastructure planning among a set of scenarios involving military and civil stakeholders. Across the infrastructure development alternatives, we identify scenarios that represent opportunities and those that represent threats. We adapt the framework of the swing weighting method for recalibration of a baseline value function with a variety of assumptions of scenarios, where each scenario is composed of one or more emergent conditions. The approach reduces the typical demand on stakeholders for elicitation of preference weights, as the entire value function is not entirely reconstructed per scenario. The approach and methodology were tested in a strategy workshop with more than 50 international participants and presented to ministry officials in a developing country. The testing integrated political, economic, environmental, and technology emergent conditions for prioritizing among infrastructure projects. Copyright © 2010 John Wiley & Sons, Ltd.

If the South Asia region hopes to meet its development goals and not risk slowing down or even halting growth, poverty alleviation, and shared prosperity, it is essential to make closing its huge infrastructure gap a priority. Identifying and addressing gaps in the data on expenditure, access, and quality are crucial to ensuring that governments make efficient, practical, and effective infrastructure development choices. This study addresses this knowledge gap by focusing on the current status of infrastructure sectors and geographical disparities, real levels of investment and private sector participation, deficits and proper targets for the future, and bottlenecks to expansion. The findings show that the South Asia region needs to invest between US$1.7 trillion and US$2.5 trillion (at current prices) to close its infrastructure gap. If investments are spread evenly over the years until 2020, the region needs to invest between 6.6 and 9.9 percent of 2010 gross domestic product per year, an estimated increase of up to 3 percentage points from the 6.9 percent of gross domestic product invested in infrastructure by countries in the region in 2009. Given the enormous size of the region's infrastructure deficiencies, it will need a mix of investment in infrastructure stock and supportive reforms to close its infrastructure gap. One major challenge will be prioritizing investment needs. Another will be choosing optimal forms of service provision, including the private sector's role, and the decentralization of administrative functions and powers.

Governments must decide how to allocate limited resources for infrastructure development, particularly since financing gaps have been projected for the coming decades. Social cost-benefit analysis provides sound project appraisal and, when systematically applied, a basis for prioritization. In some instances, however, capacity and resource limitations make extensive economic analyses across all projects unfeasible in the immediate term. This paper responds to a need for expanding the available set of tools for project selection by proposing an alternative prioritization approach that is systematic and feasible within the current resource means of government. The Infrastructure Prioritization Framework is a multi-criteria decision support tool that considers project outcomes along two dimensions, social-environmental and financial-economic. When large sets of small- to medium-sized projects are proposed, resources are limited, and basic project appraisal data (but not full social cost-benefit analysis) are available, the Infrastructure Prioritization Framework can inform project selection by combining selection criteria into social-environmental and financial-economic indexes. These indexes are used to plot projects on a Cartesian plane, and the sector budget is imposed to create a project map for comparison along each dimension. The Infrastructure Prioritization Framework is structured to accommodate multiple policy objectives, attend to social and environmental factors, provide an intuitive platform for displaying results, and take advantage of available data while promoting capacity building and data collection for more sophisticated appraisal methods and selection frameworks. Decision criteria, weighting, and sensitivity analysis should be decided and made transparent in advance of selection, and analysis should be made publicly available and open to third-party review.

Governments worldwide face the difficult challenge of deciding which infrastructure projects to prioritize and select for implementation, given the limits of available funding and the need to attain their developmental goals. The key objective of this report is to conduct a comparative exercise between the World Bank's Infrastructure Prioritization Framework, a multicriteria analysis–based methodology to project prioritization, and a more complex cost-benefit analysis–based approach. The report focuses on Chile, which has a well-institutionalized evaluation process that uses cost-benefit analysis to assess projects on their quality and ability to generate value for money. The analysis compares the results of the Infrastructure Prioritization Framework alongside Chile's current cost-benefit analysis–based and multicriteria analysis approaches to the same subsets of projects in the road transport and water reservoir subsectors, respectively. The results show that the Infrastructure Prioritization Framework has application beyond its original proposition and can complement a traditional cost-benefit analysis by directly considering social and environmental policy goals that are otherwise difficult to quantify in a cost-benefit analysis. The analysis also finds that in Chile there is a discrepancy between the stated goals and objectives of the appraisal system and the actual implementation. In the case of transport sector projects, there is an evident deviation between cost-benefit analysis–based selection policy and actual decisions made for project implementation. In the case of water catchment selection, there is a bias toward projects with higher financial-economic performance as compared to social-environmental performance, despite policy intentions to afford consideration to environmental and social development goals.

Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6's states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/pavement, and indirect damages to economic activities and regional communities that may cause loss of many lives. After disasters strike, reconstruction and maintenance of an enormous number of damaged transportation infrastructure systems require each DOT to take extremely expensive and long-term processes. In addition, planning and organizing post-disaster reconstruction and maintenance projects of transportation infrastructures are extremely challenging for each DOT because they entail a massive number and the broad areas of the projects with various considerable factors and multi-objective issues including social, economic, political, and technical factors. Yet, amazingly, a comprehensive, integrated, data-driven approach for organizing and prioritizing post-disaster transportation reconstruction projects remains elusive. In addition, DOTs in Region 6 still need to improve the current practice and systems to robustly identify and accurately predict the detailed factors and their impacts affecting post-disaster transportation recovery. The main objective of this proposed research is to develop a deep reinforcement learning-based project prioritization system for rapid post-disaster reconstruction and recovery of damaged transportation infrastructure systems. This project also aims to provide a means to facilitate the systematic optimization and prioritization of the post-disaster reconstruction and maintenance plan of transportation infrastructure by focusing on social, economic, and technical aspects. The outcomes from this project would help engineers and decision-makers in Region 6's State DOTs optimize and sequence transportation recovery processes at a regional ...

ABSTRACT Purpose: This article aims to propose an alternative methodology of analysis, assessment, and prioritization of urban mobility master projects capable of supporting investment decision-making, considering financial, economic, and space variables. Originality/value: There are no clear criteria on project proposal selection, what corroborates the critics about the selection process and prioritization of urban mobility projects in the Ministry of Cities. Intrinsically economic issues that are leveled in recent methodologies of investment and project analyses are variables considered hard to be converted into financial benefits to make up the financial evaluation. Design/methodology/approach: The methodology proposed will draw on the multidimensional scaling as a multivariate assessment tool in order to evaluate and prioritize the projects using their economic variables, the spatial variables of the urban planning, and the financial models of each project. The economic variables arise from the economic analysis available in the projects, as well as the projects' financing models. The spatial variables acquired from the social logic of space theory or spatial syntax allow the assessment of cities' integration capacity before project implementation and after their development, making it possible to identify improvements in urban mobility conditions. Findings: The use of multidimensional scaling by applying economic, financial, and spatial variables has proved to be effective in promoting decision-making, whether by indicating the best project or identifying how close and/or distant they are from the objectives of a given public policy.