Priority setting in health: origins, description and application of the Australian Assessing Cost-Effectiveness initiative

This article reports on the ‘Assessing Cost–Effectiveness’ (ACE) initiative in priority setting from Australia. It commences with why priority setting is topical and notes that a wide variety of approaches are available. In assessing these various approaches, it is argued that a useful first step is to consider what constitutes an ‘ideal’ approach to priority setting. A checklist to guide priority setting is presented based on guidance from economic theory, ethics and social justice, lessons from empirical experience and the needs of decision-makers. The checklist is seen as an important contribution because it is the first time that criteria from such a broad range of considerations have been brought together to develop a framework for priority setting that endeavors to be both realistic and theoretically sound. The checklist will then be applied to a selection of existing approaches in order to illustrate their deficiencies and to provide the platform for explaining the unique features of the ACE approach. A case study (ACE-Cancer) will then be presented and assessed against the checklist, including reaction from stakeholders in the cancer field. The article concludes with an overview of the full body of ACE research completed to date, together with some reflections on the ACE experience.

Construction supply chain modeling : a research review and interdisciplinary research agenda

Supply chain management has emerged as a popular and useful concept in the construction industry and research community since the mid 1990s. Research in construction supply chain management draws from a broad range of disciplines, notably: (1) Industrial organization economics to better understand market structure and forces and their effect on firm and supply chain behavior and (2) Analytic modeling of supply chains to improve supply chain performance along metrics such as speed, cost, reliability, quality, etc. Both industrial organization and analytic modeling provide useful but ultimately incomplete perspectives and prescriptions for construction supply chain management. As such, this paper proposes development of an interdisciplinary research agenda that draws from both fields. Towards that agenda, a review of research is presented to introduce the main ideas, relevant literature, and theory and methods in each of the two areas. From these independent reviews, applications that could benefit from a combined perspective are identified and used as a basis for development of an interdisciplinary research agenda.

Construction supply chain management : a research review and interdisciplinary research agenda

Supply chain management has emerged as a popular and useful concept in the construction industry and research community since the mid 1990s. Research in construction supply chain management draws from a broad range of disciplines, notably: (1) industrial organization economics to better understand market structure and forces and their effect on firm and supply chain behavior and (2) Analytic modeling of supply chains to improve supply chain performance along metrics such as speed, cost, reliability, quality, etc. Both industrial organization and analytic modeling provide useful but ultimately incomplete perspectives and prescriptions for construction supply chain management. As such, this paper proposes development of an interdisciplinary research agenda that draws from both fields. Towards that agenda, a review of research is presented to introduce the main ideas, relevant literature, and theory and methods in each of the two areas. From these independent reviews, applications that could benefit from a combined perspective are identified and used as a basis for development of an interdisciplinary research agenda.

The transnational corporation and new corporate citizenship theory : a critical analysis

A recent conceptualisation of corporate citizenship by Matten and Crane (2005) shifts focus onto the corporation's role in providing individuals with the rights they are entitled to as citizens. This expanded corporate role is depicted as filling an institutional vacuum resulting from the withdrawal of the state. Marking an innovation to the corporate citizenship literature, we devise a three-part analytical framework from political institutionalism to question the concept's ideological and empirical groundings. Incorporating a constrained game theory perspective, we use an example of the provision of Western corporate services by low-labour-cost nation-states to argue that the concept as strategy would in some circumstances exacerbate the implications of globalisation on individual citizenship rights. The analytical framework has application for research directed toward proposals to extend the reach of corporations in traditional public services and, more generally, for studies of corporate responsibilities. Future research on corporate citizenship would be strengthened in recognising, as we do, institutional incentives, constraints, decision-making modes and resources as used by the transnational corporation.

Dynamically opted protection envelope (DOPE) - A cost-effective strategy of insuring an investment portfolio

Popular ways of hedging downside risk of a stock portfolio is by means of a constant proportion portfolio insurance (CPPI) strategy or by means of an options-based portfolio insurance strategy (OBPI). However both have drawbacks in terms of practical applicability given transaction costs. Moreover they are not useful in times of very low liquidity e.g. in a market crash. Here we shall first review the common portfolio insurance techniques and then posit an alternative approach using a zero-coupon bond to extract downside coverage to the extent desired by an investor. While the posited strategy will not guarantee full downside protection for the entire investment horizon, it is unaffected by transaction costs resulting from need to periodically reallocate funds and is a lot easier to implement practically compared to options-based strategies. Unlike CPPI and OBPI, it will work in a crash situation too.

Low cost MPPT controller for a photovoltaic-based microgrid

 Photovoltaic based microgrid have been increasingly investigated in recent years, ascribable to their fundamental advantages such as the infinite energy source, environmentally friendly aspect and low upkeep cost. However, in practice, they are still considered as an expensive and low output option of renewable energy resources. To extract the maximum possible power from the output of the PV system, a reliable maximum power point tracker (MPPT) is required. Numerous studies have been conducted to introduce the best MPPT techniques suitable for different types of PV systems. However, they are mostly able to track the MPP from the PV system when the output signals (Voltage and Current) of individual array are available. In this study, a meta-heuristic method, based on particle swarm optimization theory, is used to determine the actual MPP of PV system, including several PV arrays, by only single current sensor at the output terminal. The results of the proposed PSO based technique, for tracking the global MPP in a multidimensional search space, have been presented at the end of this paper.

Corporate governance and corporate finance practices in a Kuwait Stock Exchange market listed firm: a survey to confront theory with practice

Purpose– This paper aims to explore the issue of corporate governance mechanisms by including the importance of stakeholders, primary objectives of the firm and the ownership of top financial managers of listed firms in Kuwait in the survey tool. It attempts to investigate whether theory aligns with the behaviour of financial managers in practice in an emerging market case.Design/methodology/approach– A survey was developed to focus primarily on the current corporate finance practices implemented by CFOs in listed companies in Kuwait. The target respondents are listed firms in the Kuwaiti Stock Exchange (KSE). The survey includes questions on topics that are closely related to capital budgeting, capital structure, cost of capital and dividend policy. For example, the survey asks the managers how they estimate their cost of equity (CAPM or other methods) and whether the impact of the weighted average cost of equity is taken into consideration in their capital structure choices.Findings– A surprising number of firms are now widely using IRR for decision making. CAPM is also in use, whereas WACC remains the most popular method used. There is some support for the “bird‐in‐hand” dividend theory in the tax‐free environment. Firms in Kuwait do not have any particular source of capital structure choices when it comes to how best to finance their projects as is the case in the US market. Firms in Kuwait are consciously striving for maximizing profits and those managers are regarded as their most important stakeholders. This may indicate the existence of agency problems.Research limitations/implications– The limitation of this study lies in the absence of empirical investigation on how corporate finance decisions may affect firms' performance in Kuwait. Hence, empirical validation will be performed by the authors in the next stage of this research, which will form the basis for further research. Empirical validation for the impact of corporate governance on performance is needed.Practical implications– This research may benefit managers and decision makers in many aspects, including having an understanding of applying popular and the most suitable corporate finance and corporate governance techniques in the management of their companies. In this research, the authors have identified the gap between practice and academia.Originality/value– To the best of the authors' knowledge, this is the first study to examine comprehensively major areas of financial policies and practices and corporate governance in an emerging market case, especially in the Middle East. Kuwait provides a unique institutional setting in its taxation system. Therefore, this study will make a contribution to the general literature in this field.

A decentralized cloud firewall framework with resources provisioning cost optimization

Cloud computing is becoming popular as the next infrastructure of computing platform. Despite the promising model and hype surrounding, security has become the major concern that people hesitate to transfer their applications to clouds. Concretely, cloud platform is under numerous attacks. As a result, it is definitely expected to establish a firewall to protect cloud from these attacks. However, setting up a centralized firewall for a whole cloud data center is infeasible from both performance and financial aspects. In this paper, we propose a decentralized cloud firewall framework for individual cloud customers. We investigate how to dynamically allocate resources to optimize resources provisioning cost, while satisfying QoS requirement specified by individual customers simultaneously. Moreover, we establish novel queuing theory based model M/Geo/1 and M/Geo/m for quantitative system analysis, where the service times follow a geometric distribution. By employing Z-transform and embedded Markov chain techniques, we obtain a closed-form expression of mean packet response time. Through extensive simulations and experiments, we conclude that an M/Geo/1 model reflects the cloud firewall real system much better than a traditional M/M/1 model. Our numerical results also indicate that we are able to set up cloud firewall with affordable cost to cloud customers.

A highly practical approach toward achieving minimum data sets storage cost in the cloud

Massive computation power and storage capacity of cloud computing systems allow scientists to deploy computation and data intensive applications without infrastructure investment, where large application data sets can be stored in the cloud. Based on the pay-as-you-go model, storage strategies and benchmarking approaches have been developed for cost-effectively storing large volume of generated application data sets in the cloud. However, they are either insufficiently cost-effective for the storage or impractical to be used at runtime. In this paper, toward achieving the minimum cost benchmark, we propose a novel highly cost-effective and practical storage strategy that can automatically decide whether a generated data set should be stored or not at runtime in the cloud. The main focus of this strategy is the local-optimization for the tradeoff between computation and storage, while secondarily also taking users' (optional) preferences on storage into consideration. Both theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications with Amazon's cost model show that the cost-effectiveness of our strategy is close to or even the same as the minimum cost benchmark, and the efficiency is very high for practical runtime utilization in the cloud.