Journal of Infrastructure Systems

A distance-based highway pricing scheme has been considered a means to tackle highway revenue shortfalls as an alternative to the current taxation on motor fuels. To establish fee rates for a distance-based pricing scheme, this study argues that maintenance and management of the highway system be self-financed by its users, who are responsible for maintenance, repair, and rehabilitation of the highway system. Each user’s highway cost responsibility is determined by its vehicle class, road functional class, types and frequency of interventions, and other technical parameters. This paper uses the State Highway Cost Allocation Study (HCAS) tool to analyze expenditures, revenues, and usages of a state highway system to obtain cost borne by various user groups. On the basis of Indiana State Highway data, cost responsibility of each highway user varies between $0.66¢/\mathrm{km}$ and $25.05¢/\mathrm{km}$ among 20-vehicle types. Sensitivity analysis was carried out considering several technical parameters including load equivalency factor, non-load-related impacts on pavement, and minimum requirements for construction and rehabilitation to reveal the reasonable ranges of cost responsibility of different users.

Infrastructure sectors such as energy or water supply, sanitation, or telecommunications provide us with services that are essential for modern life and for industrialized societies. In this article, we explore some of the sectors’ key characteristics in order to better understand the conditions that stimulate or hinder far-reaching transformation processes in infrastructures. It will be argued that durable and capital-intensive assets, together with a high degree of systemness generate considerable inertia and impede fundamental change. At the same time, capital intensity and massive investment needs as well as negative environmental impacts represent sources for change. A high degree of regulation and an often large share of public utilities also play a key role for sector dynamics. Conceptual frameworks for studying infrastructures and making policy recommendations have to take into account these particularities and the close interplay of techno-economic, organizational, and institutional characteristics.

This paper analyzes the contribution of public infrastructure to private sector. It takes the example of road and rail and investigates their impact on South Korean manufacturing industries. To assess the cost structure and efficiency of investments in infrastructure, economies of scale, effects of infrastructure on variable cost and output, investment condition for infrastructure, and substitution and price elasticities are calculated. The divergence of infrastructure stocks from their static equilibrium levels influences production efficiency. Overall, investments in road and rail have positive effects on the manufacturing industries in Korea. This study expands the scope of existing studies by decomposing the internal rate of return (IRR) and the present value of benefit ($B_{PV}$) into variable cost reduction, investment cost reduction, and rent. It was found that $B_{PV}$ checks only the magnitude of benefit, whereas IRR indicates the existence of efficiency by investigating total cost reduction and rent. Finally, by analyzing investment efficiency and changing benefit with respect to road and rail through the investment efficiency methodology that compares IRR with market interest rate, retrospective benefit-cost analysis is conducted.

Adoption of a suitable sewer pipeline condition classification protocol is recognized as an indispensable first step in worldwide sewer rehabilitation industry. Various condition classification systems for sewers have been developed in this regard. These systems differ according to local requirements in which no integrated and unified sewer condition assessment protocol is available. Therefore, an urgent need exists to develop standardized sewer condition assessment procedures. The presented research in this paper aims to review the historical development of different sewer condition classification protocols and develop a combined condition index (CCI) for sewers that integrates the combined effect of structural and operational conditions. To achieve these objectives, unsupervised neural network models have been developed. The CCI is divided into five condition categories ranging from “acceptable” to “critical.” An unsupervised, self-organizing, neural network approach is also used to develop the CCI. The opinion of municipal practitioners is utilized to verify the CCI and integrated protocol. The developed integrated models and protocols will assist municipal engineers in developing a unified sewer condition assessment system. An unsupervised neural network methodology is adapted for integrating sewer condition assessment protocols and developing the CCI of sewer pipelines. The protocols developed by the Water Research Centre (WRc), United Kingdom, and the Centre for Expertise and Research on Infrastructures in Urban Areas (CERIU), Canada, have been used for the modeling process.