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The Environmental Protection Bureau of Taiwan established the South Star Project in Kaohsiung, Taiwan, as a solution to two problems facing the city—the urgent need to dispose of industrial wastes and the need to increase land for the city. To embank land from the sea, breakwaters were constructed. The material used to construct breakwaters was a mixture of furnace slag (waste from the steel industry) and fly ash (waste from power plants). After constructing the breakwaters, the ‘reclaimed land’ was used as a landfill for construction and public waste. In the future, these reclaimed lands will be used for the development of a deepwater port or sea airport. Construction of breakwaters is a very repetitive process, and any improvements made would help contractors reduce the duration of the operation, improve efficiency in the process and thereby reduce costs. This paper discusses the process of breakwater construction and the utilization of industrial wastes for the concrete work on the project. Data collected from the first stage of the South Star Project is used in the modelling, simulation and analysis of the process, in order to examine the interaction between different resources.

Since the early 1960s, there have been different techniques to schedule linear projects, but for the most part, these have been overshadowed by the critical path method (CPM). Recently, there has been renewed interest in linear scheduling and in adapting some of the CPM techniques to linear scheduling. This necessitates a review of the research in the area of linear scheduling. The present paper provides an overview of linear scheduling, discusses the different approaches that have been used and expresses new avenues for research in the area of resource levelling of linear schedules.

Finding the optimal solution to address problems in sewer management systems has always challenged asset managers. An understanding of deterioration mechanisms in sewers can help asset managers in developing prediction models for estimating whether or not sewer collapse is likely. The effective use of deterioration prediction models along with the development and use of life cycle cost analysis (LCCA) can contribute to the goals of reducing construction, operation and maintenance costs in sewer systems. When sewer system maintenance/rehabilitation options are viewed as investment alternatives, it is important, and in some cases, imperative, to make decisions based on life cycle costs instead of relying totally on initial construction costs. The objective of this paper is to discuss the application of deterioration modelling and life cycle cost principles in sewer system management, and to explore the role of the Markov chain model in decision making regarding sewer rehabilitation. A test case is used to demonstrate the application of the Markov chain decision model for sewer system management. The analysis includes evaluation of this concept using dynamic programming and the policy improvement algorithm.

This paper proposes a decision‐making framework to assist asset managers in decision making regarding sewer maintenance/rehabilitation (M&R) plans under constraints of limited access to sewer condition data. It discusses the application of probabilistic dynamic programming in conjunction with a Markov chain model to analyze the life cycle cost of combined sewer systems. M&R issues have traditionally been addressed with a crisis‐based approach, but this study contributes to sewer infrastructure management efforts in developing a management system based on life cycle cost analysis. The framework includes the optimal M&R techniques for sewer projects and the optimal times of application. The role of simulation is also explored to obtain the variability of the total cost. By knowing the expected costs and their variabilities, a deeper understanding of life cycle costs of sewer infrastructure can be obtained. The model’s capability is enhanced further by testing its sensivitity to varying discount and inflation rates.

The purpose of this paper is to present a methodology to evaluate the capital investments in infrastructure projects managed by private operators considering uncertainties in the operation and maintenance of the infrastructure components.

The methodology described in this paper is based on two major sources of information: deterioration curves of the infrastructure systems obtained from Markov chain models and the value of flexibility obtained from a real options analysis.

Using this methodology, it is possible to determine whether there is value if project managers adopt flexible strategies in determining capital investments. These strategies refer to the opportunities of postponing, deferring or canceling capital investments required to maintain the operation of the infrastructure systems.

The model utilizes Monte Carlo simulation and real options analysis to overcome the complexities associated with the solution of the differential equations that represent the variability of the main factors in the project cash flow.

The methodology presented in this paper can be used by public officials, private investors, and asset managers to determine the value of flexibility associated with the strategies required to maintain the operation of infrastructure assets.

The purpose of the study presented in this paper is to assess determinants of financial innovations in infrastructure using a system‐of‐systems approach, and to demonstrate this approach in the context of the US highway transportation sector.

A system‐of‐systems approach is adopted for systemic assessment. Data obtained from a case‐based research approach and a survey deployed to the state Departments of Transportation in the US is utilized in parallel with a network analysis to explore the status quo, key players and interactions, and the drivers of financial innovations for infrastructure.

The findings include constructs regarding the players, practices, and activities and also a conceptual model relating to the drivers of financial innovations.

The model along with the constructs provides an analytical tool for understanding the dynamics of financial innovations. Such understanding would lead to expansion of the creation and diffusion of financial innovation practices in the highway transportation infrastructure globally.

The study presented in this paper is the first of its kind to identify the determinants of financial innovations in infrastructure based on a systemic approach.

Due to the growing demand for civil infrastructure, financial innovations are required to close the financing gap. However, a lack of theories has inhibited a complete understanding and, thus, creation and diffusion of financial innovation. A lack of theory about financial innovations in infrastructure is mainly due to the absence of a framework to conceptualize these innovations. A typology that enables comparison of financial systems and, hence, provide a framework to conceptualize financial innovations is missing in the existing literature. This paper defines innovation in the context of financing, funding and delivery of infrastructure projects and proposes a new typology for conceptualization of the loci and types of financial innovations in infrastructure. The loci of innovations are in risk mitigation, regulation, cash flow, contract, organizational, and capital sub-systems. Types of innovations are classified as either integrated or modular and either sustaining or disruptive. The typology was tested by mapping seven innovations created by the U. S. Federal Highway Administration and diffused into 232 transportation projects between 1994 and 2002. Qualitative comparative analysis was then used to evaluate the diffusion trends of financial innovations in the case studies and to demonstrate the capability of the proposed typology for facilitating theory building in the area of infrastructure financial innovations.