The opportunity for implementing Islamic project financing to the Indonesian infrastructure development

Purpose: This chapter discusses the opportunity of Islamic project financing implementation for public infrastructure development in Indonesia. Design/Methodology/Approach: This chapter, firstly, reviewed existing literature on Islamic finance to explore the applicability of Islamic financing in infrastructure development. Interviews were conducted as the first stage of Delphi method approach. This was then followed by reviewing Indonesia’s government policies and regulations in infrastructure industry and Islamic financing. Findings: This chapter enlightens the implementation of Islamic financing on infrastructure project financing in Indonesia. The findings indicate that the government policies and regulations on both infrastructure investment and Islamic financing support the implementation of Islamic project financing, whereas, an improvement is still needed in order to overarch infrastructure business and Islamic financing investment. Research: Financing framework development for Indonesia infrastructure projects. Limitations/Implications: The result reported comprises the preliminary study of Islamic project paper written based on published research papers and interviews. Furthermore, the data collected for the study are limited to the case of Indonesian infrastructure projects. Practical Implication: Islamic financing in Indonesia infrastructure projects development has not been optimally implemented. Therefore, this chapter serves as a catalyst to explore alternative financial scheme such as Islamic financing for infrastructure development. Originality/Value: This chapter highlights possibilities and obstacles in applying Islamic scheme to infrastructure project financing. This provides a framework to analyse the steps to implement Islamic financing successfully in infrastructure development.

Time and cost performance of design–build projects

The design-build (DB) delivery method has been widely used in the United States due to its reputed superior cost and time performance. However, rigorous studies have produced inconclusive support and only in terms of overall results, with few attempts being made to relate project characteristics with performance levels. This paper provides a larger and more finely grained analysis of a set of 418 DB projects from the online project database of the Design-Build Institute of America (DBIA), in terms of the time-overrun rate (TOR), early start rate (ESR), early completion rate (ECR) and cost overrun rate (COR) associated with project type (e.g., commercial/institutional buildings and civil infrastructure projects), owners (e.g., Department of Defense and private corporations), procurement methods (e.g., ‘best value with discussion’ and qualifications-based selection), contract methods (e.g., lump sum and GMP) and LEED levels (e.g., gold and silver). The results show ‘best value with discussion’ to be the dominant procurement method and lump sum the most frequently used contract method. The DB method provides relatively good time performance, with more than 75% of DB projects completed on time or before schedule. However, with more than 50% of DB projects cost overrunning, the DB advantage of cost saving remains uncertain. ANOVA tests indicate that DB projects within different procurement methods have significantly different time performance and that different owner types and contract methods significantly affect cost performance. In addition to contributing to empirical knowledge concerning the cost and time performance of DB projects with new solid evidence from a large sample size, the findings and practical implications of this study are beneficial to owners in understanding the likely schedule and budget implications involved for their particular project characteristics.

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

FleSSR project: Sustainable business models for community cloud infrastructure in the UK higher education sector

Cloud-based infrastructure essentially comprises two offerings, cloud-based compute and cloud-based storage. These are perhaps best typified for most people by the two main components of the Amazon Web Services (AWS)1 public cloud offer, the Elastic Compute Cloud (EC2)2 and the Simple Storage Service (S3)3, though, of course, there are many other related services offered by Amazon and many other providers of similar public cloud infrastructure across the Internet.

Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Measuring Web Performance in the Wide Area

One of the most vexing questions facing researchers interested in the World Wide Web is why users often experience long delays in document retrieval. The Internet's size, complexity, and continued growth make this a difficult question to answer. We describe the Wide Area Web Measurement project (WAWM) which uses an infrastructure distributed across the Internet to study Web performance. The infrastructure enables simultaneous measurements of Web client performance, network performance and Web server performance. The infrastructure uses a Web traffic generator to create representative workloads on servers, and both active and passive tools to measure performance characteristics. Initial results based on a prototype installation of the infrastructure are presented in this paper.

Computer simulation of VLTA evacuation performance: a report from the VERRES project

This paper reports on research work undertaken for the European Commission funded study GMA2/2000/32039 Very Large Transport Aircraft (VLTA) Emergency Requirements Research Evacuation Study (VERRES). A particular focus was on evacuation issues with a detailed study of evacuation performance using computer models being undertaken as part of Work Package 2. This paper describes this work and investigates the use of internal stairs during evacuation using computer simulation.

An analysis of passenger performance on stairs and upper deck slides during evacuation trials: a report from the VERRES project

This paper reports on research work undertaken for the European Commission funded study GMA2/2000/32039 Very Large Transport Aircraft (VLTA) Emergency Requirements Research Evacuation Study (VERRES). A particular focus of VERRES was on evacuation issues and several large-scale evacuation trials were conducted in the CRANFIELD simulator. This paper addresses part of the research undertaken for Work Package 3 by the University of Greenwich with a focus on the analysis of the data concerning passenger use of stairs and passenger exit hesitation time analysis for upper deck slides.