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.

Operating efficiency and return to scale of Malaysian REITS: The preliminary findings

This paper aims to present preliminary findings on measuring the technical efficiencies using Data Envelopment Analysis (DEA) in Malaysian Real Estate Investment Trusts (REITs) to determine the best practice for operations which include the asset allocation and scale size to improve the performance of Malaysian REITs. Variables identified as input and output will be assessed in this cross section analysis using the operational approach and Variable Return to Scale DEA (VRS-DEA) by focusing on Malaysian REITs for the year 2013. Islamic REITs have higher efficiency score as compared to the conventional REITs for both models. Diversified REITs are more efficient as compared to the specialised REIT using both models. For Model 1, the negative inefficient value is identified in the managerial inefficiency as compared to the scale inefficiency. This shows that inputs are not fully minimised to produce more outputs. However, when other expenses are considered as different input variables, the efficiency score becomes higher from 60.3% to 81.2%. In model 2, scale inefficiency produce greater inefficiency as compared to the managerial efficiency. The result suggests that Malaysian REITs have been operating at the wrong scale of operations as majority of the Malaysian REITs are operating at decreasing return to scale.

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

Ink-jet printing of graphene for flexible electronics: An environmentally-friendly approach

Mechanical flexibility is considered an asset in consumer electronics and next-generation electronic systems. Printed and flexible electronic devices could be embedded into clothing or other surfaces at home or office or in many products such as low-cost sensors integrated in transparent and flexible surfaces. In this context inks based on graphene and related two-dimensional materials (2DMs) are gaining increasing attention owing to their exceptional (opto)electronic, electrochemical and mechanical properties. The current limitation relies on the use of solvents, providing stable dispersions of graphene and 2DMs and fitting the proper fluidic requirements for printing, which are in general not environmentally benign, and with high boiling point. Non-toxic and low boiling point solvents do not possess the required rheological properties (i.e., surface tension, viscosity and density) for the solution processing of graphene and 2DMs. Such solvents (e.g., water, alcohols) require the addition of stabilizing agents such as polymers or surfactants for the dispersion of graphene and 2DMs, which however unavoidably corrupt their properties, thus preventing their use for the target application. Here, we demonstrate a viable strategy to tune the fluidic properties of water/ethanol mixtures (low-boiling point solvents) to first effectively exfoliate graphite and then disperse graphene flakes to formulate graphene-based inks. We demonstrate that such inks can be used to print conductive stripes (sheet resistance of ~13 kΩ/□) on flexible substrates (polyethylene terephthalate), moving a step forward towards the realization of graphene-based printed electronic devices.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Enhancing information about sustainability features for sustainable housing delivery

Sustainability practices in government regulations and within the society influence the delivery of sustainable housing. The actual delivery rate of Australian sustain-able housing is not as high as other countries. There is an absence of engagement by stakeholders in adopting sustainable housing practices. This may be due, in the current Australian property market, to confusion as to what sustainability features should be considered, given the large range of environmental, economic and social sustainability options possible. One of the main problems appears to be that information demanders, especially real estate agents, valuers, insurance agents and mortgage lenders do not include sustainability perspectives in their advice or in their decision processes. Information distribution in the Australian property market is flawed, resulting in a lack of return-on-investment value of ‘green’ features implemented by some stakeholders. This paper reviewed the global sustainable development concept and Australian sustainable assessment methods. This review identified the possibility of a research project which aimed at identifying and integrating different perceptions and priority needs of the information demanders, for developing a model for the potential implementation of sustainability features distribution in the property industry. This research will reduce confusion on the sustainability-related information which can influence the decision making of stakeholders in the supply and demand of sustainable housing.

New Generation Rollingstock Depot: Case Study Report

This report summarises the findings of a case study on Queensland’s New Generation Rollingstock (NGR) Project carried out as part of SBEnrc Project 2.34 Driving Whole-of-life Efficiencies through BIM and Procurement. This case study is one of three exemplar projects studied in order to leverage academic research in defining indicators for measuring tangible and intangible benefits of Building Information Modelling (BIM) across a project’s life-cycle in infrastructure and buildings. The NGR is an AUD 4.4 billion project carried out under an Availability Payment Public-Private Partnership (PPP) between the Queensland Government and the Bomabardier-led QTECTIC consortium comprising Bombardier Transportation, John Laing, ITOCHU Corporation and Aberdeen Infrastructure Investments. BIM has been deployed on the project from conceptual stages to drive both design and the currently ongoing construction at the Wulkuraka Project Site. This case study sourced information from a series of semi-structured interviews covering a cross-section of key stakeholders on the project. The present research identified 25 benefits gained from implementing BIM processes and tools. Some of the most prominent benefits were those leading to improved outcomes and higher customer satisfaction such as improved communications, data and information management, and coordination. There were also a number of expected benefits for future phases such as: • Improved decision making through the use of BIM for managing assets • Improved models through BIM maturity • Better utilisation of BIM for procurement on similar future projects • New capacity to specify the content of BIM models within contracts There were also three benefits that were expected to have been achieved but were not realised on the NGR project. These were higher construction information quality levels, better alignment in design teams as well as project teams, and capability improvements in measuring the impact of BIM on construction safety. This report includes individual profiles describing each benefit as well as the tools and processes that enabled them. Four key BIM metrics were found to be currently in use and six more were identified as potential metrics for the future. This case study also provides insights into challenges associated with implementing BIM on a project of the size and complexity of the NGR. Procurement aspects and lessons learned for managers are also highlighted, including a list of recommendations for developing a framework to assess the benefits of BIM across the project life-cycle.

An experimental analysis of information acquisition in prediction markets

We study which factors in terms of trading environment and trader characteristics determine individual information acquisition in experimental asset markets. Traders with larger endowments, existing inconclusive information, lower risk aversion, and less experience in financial markets tend to acquire more information. Overall, we find that traders overacquire information, so that informed traders on average obtain negative profits net of information costs. Information acquisition and the associated losses do not diminish over time. This overacquisition phenomenon is inconsistent with predictions of rational expectations equilibrium, and we argue it resembles the overdissipation results from the contest literature. We find that more acquired information in the market leads to smaller differences between fundamental asset values and prices. Thus, the overacquisition phenomenon is a novel explanation for the high forecasting accuracy of prediction markets.

Electricity pricing in New Zealand and the Australian State of Queensland: Accounting for the impact of sector restructuring

The electricity industries of New Zealand (NZ) and the Australian state of Queensland have undergone substantial structural and regulatory reform with the common intent to improve economic efficiency. Deregulation and privatisation have been key elements of the reform but have been approached differently by each jurisdiction. This study traces the link between structural and regulatory regimes and asset valuation, profits and, ultimately, pricing. The study finds that key drivers in recent price increases are the government-owned generation and retail sector in NZ and the government-owned distribution sector in Queensland. It is concluded that, contrary to the rationale for the imposition of regulatory controls in a nonmarket environment, the regulatory regimes appear to have contributed to higher rather than lower pricing structures.

Fair value accounting for non-current assets and audit fees: Evidence from Australian companies

We investigate the association between asset revaluations of non-current assets and audit fees, using a sample of ASX 300 companies from the years 2003–2007.We report that there is a significant increase in the audit fees paid when non-financial assets (PPEs, investment properties and intangible assets) are measured at fair values. Moreover, we provide evidence that an independent valuer or appraiser significantly weakens the positive association between asset revaluations and audit fees. Furthermore, companies whose noncurrent assets are revalued upwards and those that revalue their non-current assets upwards every year have significantly higher audit fees. Additional tests provide empirical evidence that the strength of corporate governance has a moderating effect on the level of audit fees. This study contributes to the ongoing debate on the role of fair value accounting. The findings suggest agency costs associated with fair value estimates may offset the benefits from the use of fair value accounting.

Government entity contribution to an effective partnership privatisation

The partnership form of privatisation is increasingly being used, in particular to carry out complex and evolving bundles of services. These have not previously been privatised because of incomplete contracts and contract management difficulties. Improved performance of the government entity as contract administrator and member of the partnership is crucial to modern service delivery expectations yet the privatisation literature has focused on other aspects of partnerships leaving the understanding of factors impacting the effectiveness of the government entity underdeveloped. This paper proposes the development of knowledge as to the range of factors which impact the effectiveness of the government entity. There is limited data available as to the operation of trust in the partnership relationship, and as to the capability of a range of privatisation forms to achieve stewardship of infrastructure. This research will utilise the findings from that research to build a tentative framework which will be utilised in staged research interrogating first the privatization literature and then the literature of other disciplines and sectors. The combined data will be analysed to provide government and practitioners such as government entity CEO’s with a complete listing of the operation of the factors which impact the effectiveness of the government entity in contributing to improved service delivery.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Making and changing wills: Prevalence, predictors, and triggers

Wills are important social, economic, and legal documents. Yet little is known about current will making practices and intentions. A comprehensive national database on the prevalence of will making in Australia was developed to identify who is or is not most likely to draw up a will and triggers for making and changing wills. A national survey of 2,405 adults aged above 18 years was administered by telephone in August and September 2012. Fifty-nine percent of the Australian adult population has a valid will, and the likelihood of will making increases with age and estate value. Efforts to get organized, especially in combination with life stage and asset changes trigger will making; procrastination, rather than a strong resistance, appears to explain not making a will. Understanding will making is timely in the context of predicted significant intergenerational transfers of wealth, changing demographics, and a renewed emphasis on retirement planning.

A heterogeneous computing approach to simulation of the Heston Stochastic Volatility Model

Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

Driving whole-of-life efficiencies through BIM and procurement

Building Information Modelling (BIM) is a digital process that encompasses all aspects, disciplines and systems of built assets within a single virtual model. This allows stakeholders to collaborate more accurately and efficiently than with traditional processes. Case study 1 Design: New Generation Rollingstock Maintenance Centre, Queensland. Case Study 2 Construction: Perth Children's Hospital, Western Australia. Case Study 3 Asset Management: Sydney Opera House, New South Wales. This project sought to provide the built environment industry with a framework to measure and maximize benefits from implementing BIM across the life-cycle phases of a built asset.