Modelling optimal risk allocation in PPP projects using artificial neural networks

This paper aims to establish, train, validate, and test artificial neural network (ANN) models for modelling risk allocation decision-making process in public-private partnership (PPP) projects, mainly drawing upon transaction cost economics. An industry-wide questionnaire survey was conducted to examine the risk allocation practice in PPP projects and collect the data for training the ANN models. The training and evaluation results, when compared with those of using traditional MLR modelling technique, show that the ANN models are satisfactory for modelling risk allocation decision-making process. The empirical evidence further verifies that it is appropriate to utilize transaction cost economics to interpret risk allocation decision-making process. It is recommended that, in addition to partners' risk management mechanism maturity level, decision-makers, both from public and private sectors, should also seriously consider influential factors including partner's risk management routines, partners' cooperation history, partners' risk management commitment, and risk management environmental uncertainty. All these factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects.

A social network analysis model for analysing stakeholder-associated safety risks in infrastructure projects

An important strategy in the long-term blueprint for making Australia's 18 capital and major regional cities more productive, sustainable and liveable is to develop high quality public infrastructure systems to improve civic quality of life. Because of the unique features of construction activities, such as long period, complicated processes, and dynamic organizational structures, infrastructure projects normally involve multiple stakeholders and are subject to various risks, especially safety issues. Any negligence or mismanagement of critical safety risks will have huge impact on achieving project objectives and success. Although many previous studies have identified and assessed various safety risks in construction industry, a main research gap is that these studies ignored a fact that most risks are interrelated and associated with internal and external stakeholders of the projects. The lack of a theoretical foundation and appropriate methods for analysing stakeholder-associated safety risks and their interdependencies in infrastructure projects hinders effective risk management processes and the formulations of decision strategies. This research aims at enabling higher performance in strategic safety risk management in infrastructure projects through the development of a holistic risk analysis model using Stakeholder and Social Network Theories. The outcomes can broaden project managers' awareness of emerging influential safety risks and enhance their ability to perceive, understand, assess, and mitigate safety risks in an effective and efficient way; thereby higher performance in strategic risk management could be achieved in infrastructure projects.

Cost and time overruns in commercial construction projects : an Australian study

Cost and schedule are two of most important performance indicators of construction projects. Cost escalation and time overruns are typically associated with poor management practices. Cost overruns and delays have huge impacts on construction projects in relation to the costs of a project, the reputation of the parties involved, and the satisfaction of the final product. Therefore, it is imperative to understand the causes of cost and time overruns so that mitigation measures can be set in place. A group of industry professionals in South Australia were surveyed on their perceptions of the factors contributing towards the cost and time overruns in commercial construction projects. The results showed that timeliness of decision making is ranked as the top factor contributing towards delays whereas problems with design is perceived as most influential to the cost overruns. In addition, the questionnaire survey found that different parties, i.e. clients, contractors and consultants have different perceptions on the impacts of these factors. Similarly, the structural frame stage was considered the most critical stage for controlling the time and cost performance during the construction process. Implications are discussed.

A comparative study of effectiveness of peer assessment of individuals’ contributions to group projects in undergraduate construction management core units

In recent years, various forms of group work have been introduced in university courses across various subject domains, including construction management courses. Although the use of group work in higher education has sound pedagogical reasons and advantages, group work has its own drawbacks. Therefore, the acceptance by students and the success of group work critically depend on a fair and credible assessment of the group process. In this paper, the implementation of different approaches to peer assessment (PA) of individuals’ contributions to group projects in two core units in an undergraduate construction management course in an Australian university is reported. The effectiveness of the adopted PA approaches have been evaluated and validated by students. It has been found that contrary to doubts of the sufficiency of a simplistic approach to PAs, the fairness of a PA approach does not necessarily depend on its complexity. Besides, voluntary group discussions, learning and collaboration are found to aid in improving each of the group’s camaraderie. Hence, it is recommended that academics should develop both a structured methodology to progressively encourage group members to work cohesively in teams and effective PA approaches that measure individual member’s contribution.

Critical uncertainty factors for efficient risk allocation in privately financed public infrastructure projects in Australia

Risk allocation in privately financed public infrastructure projects, commonly referred to as public-private partnership (PPP) projects, is a challenging job due to the nature of incomplete contracting. Choosing a risk allocation strategy could be viewed as the process of deciding the proportion of risk management attributable to the public and private partners based on a series of characteristics of the risk management service transaction in question. These characteristics can be related to the various uncertainty factors. In this study, uncertainty factors have been grouped into Institutional, Social and industrial, Economic, and Project-specific categories and examined in order to achieve efficient risk allocation and minimize risk management-related costs in a long-term view. Critical uncertainty factors for the allocation of three major risks have been identified through an industry-wide survey in Australia. These identified critical uncertainty factors are expected to help decision-makers from both public and private sectors choose efficient allocation strategies for major risks. Future research directions are also set out.

Critical uncertainty factors for efficient allocation of demand risk in privately financed public infrastructure projects in Australia

Risk allocation in privately financed public infrastructure projects, which are mainly referred as public-private partnership (PPP) projects, is a challenging job due to the nature of incomplete contracting. Among the various risks that may eventually materialise, demand risk is one of the major challenges that PPPs face. Choosing a risk allocation strategy could be viewed as the process of deciding the proportion of risk management responsibility between public and private partners based on a series of characteristics of risk management service transaction in question. These characteristics are more or less related to the various uncertainty factors. In this study, various uncertainty factors have been examined in order to achieve efficient allocation of demand risk and minimise risk management-related costs in a long-term view. Critical uncertainty factors have been identified through an industry-wide survey in Australia. Future research directions are also set out.

Factor analysis of partners' commitment to risk management in public-private partnership projects

Purpose – The purpose of this paper is to investigate and uncover key determinants that could explain partners' commitment to risk management in public-private partnership projects so that partners' risk management commitment is taken into the consideration of optimal risk allocation strategies.

Design/methodology/approach – Based on an extensive literature review and an examination of the purchasing power parity (PPP) market, an industry-wide questionnaire survey was conducted to collect the data for a confirmatory factor analysis. Necessary statistical tests are conducted to ensure the validity of the analysis results.

Findings – The factor analysis results show that the procedure of confirmatory factor analysis is statistically appropriate and satisfactory. As a result, partners' organizational commitment to risk management in public-private partnerships can now be determined by a set of components, namely general attitude to a risk, perceived one's own ability to manage a risk, and the perceived reward for bearing a risk.

Practical implications – It is recommended, based on the empirical results shown in this paper, that, in addition to partners' risk management capability, decision-makers, both from public and private sectors, should also seriously consider partners' risk management commitment. Both factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects. Future research may therefore explore how to form optimal risk allocation strategies by integrating organizational capability and commitment, the determinants and measurement of which have been established in this study.

Originality/value – This paper makes an original contribution to the general body of knowledge on risk allocation in large-scale infrastructure projects in Australia adopting the procurement method of public-private partnership. In particular, this paper has innovatively established a measurement model of organisational commitment to risk management, which is crucial to determining optimal risk allocation strategies and in turn achieving project success. The score coefficients of all obtained components can be used to construct components by linear combination so that commitment to risk management can be measured. Previous research has barely focused on this topic.

Conservation cornerstones : capitalising on the endeavours of long-term monitoring projects

Ecological monitoring is widely used to measure change through time in ecosystems. The current extinction crisis has resulted in a wealth of monitoring programs focussed on tracking the status of threatened species, and the perceived importance of monitoring has seen it become the cornerstone of many biodiversity conservation programs. However, many monitoring programs fail to produce useful outcomes due to inherent flaws. Here we use a monitoring program from south-eastern Australia as a case study to illustrate the potential of such endeavours. The threatened carnivorous marsupial, the brush-tailed phascogale (Phascogale tapoatafa), has been monitored at various locations between 2000 and 2010. We present strong evidence for a decline in relative abundance during this period, and also describe relationships with environmental variables. These results provide insights likely to be valuable in guiding future management of the species. In the absence of the monitoring program, informed management would not be possible. While early detection of population declines is important, knowledge of the processes driving such declines is required for effective intervention. We argue that monitoring programs will be most effective as a tool for enhanced conservation management if they test specific hypotheses relating to changes in population trajectories. Greater emphasis should be placed on rigorous statistical analysis of monitoring datasets in order to capitalise on the resources devoted to monitoring activities. Many datasets are likely to exist for which careful analysis of results would have benefits for determining management directions.