Major quantitative techniques for risk analysis in the construction industry : a comparative analysis

Risk analysis is one of the critical functions of the risk management process. It relies on a detailed understanding of risks and their possible implications. Construction projects, because of their large and complex nature, are plagued by a variety of risks which must be considered and responded to in order to ensure project success. This study conducts an extensive comparative analysis of major quantitative risk analysis techniques in the construction industry. The techniques discussed and comparatively analyzed in this report include: Programme Evaluation and Review Technique (PERT), Judgmental Risk Analysis Process (JRAP), Estimating Using Risk Analysis (ERA), Monte Carlo Simulation technique, Computer Aided Simulation for Project Appraisal and Review (CASPAR), Failure Modes and Effects Analysis technique (FMEA) and Advanced Programmatic Risk Analysis and Management model (APRAM). The findings highlight the fact that each risk analysis technique addresses risks in any or all of the following areas – schedule risks, budget risks or technical risks. Through comparative analysis, it has been revealed that a majority of risk analysis techniques focus on schedule or budget risks. Very little has been documented in terms of technical risk analysis techniques. In an era where clients are demanding and expecting higher quality projects and finishes, project managers must endeavor to invest time and resources to ensure that the few existing technical risk analysis techniques are developed and further refined, and that new technical risk analysis techniques are developed to suit the current construction industries requirements.

Global positioning systems in the AFL : worthwhile or waste of time?

Global Positioning Systems (GPS) in the Australian Football League (AFL) are the big-ticket item that sees clubs trying to gain any competitive advantage over their opposition that they can. This paper explores whether the current application of GPS by clubs is worthwhile or a waste of time from three core perspectives: technical, organisational and personal. Issues include poor data storage and analysis, inaccurate units, lack of appropriate business processes in place, and resistance to use. Although many of these issues can be addressed through improved technology, resolving the organisational and personal issues will require a change in mindset to ensure the use of GPS in the AFL is a worthwhile endeavour. The paper concludes that the current use of GPS devices in the AFL is a waste of time.

Stakeholder participation in estuary management: the development of Victoria's Estuary Entrance Management Support System

Stakeholder involvement in the management of estuaries is a necessary element of good environmental governance. In Victoria, Australia, a key challenge for estuary managers is whether or not estuaries should be artificially opened since many river mouths close ‘naturally’ from time to time. Estuary closure resulting in raised estuarine water levels leads to economic and social impacts on local communities. In the past these effects have been addressed by artificial river mouth openings, often without reference to associated environmental impacts. This article discusses the development and features of an Estuary Entrance Management Support System and considers its performance against principles of effective environmental management. It concludes that, in bringing together technical information with stakeholder input through a structured process, such a system makes a useful contribution to improving estuary entrance management.

New frontiers in biologging science

The term ‘biologging’ refers to the use of miniaturized animal-attached tags for logging and/or relaying of data about an animal's movements, behaviour, physiology and/or environment. Biologging technology substantially extends our abilities to observe, and take measurements from, free-ranging, undisturbed subjects, providing much scope for advancing both basic and applied biological research. Here, we review highlights from the third international conference on biologging science, which was held in California, USA, from 1 to 5 September 2008. Over the last few years, considerable progress has been made with a range of recording technologies as well as with the management, visualization, integration and analysis of increasingly large and complex biologging datasets. Researchers use these techniques to study animal biology with an unprecedented level of detail and across the full range of ecological scales—from the split-second decision making of individuals to the long-term dynamics of populations, and even entire communities. We conclude our report by suggesting some directions for future research.

Categorization of disaster decision support needs for the development of an integrated model for DMDSS

The wide variety of disasters and the large number of activities involved have resulted in the demand for separate Decision Support System (DSS) models to manage different requirements. The modular approach to model management is to provide a framework in which to focus multidisciplinary research and model integration. A broader view of our approach is to provide the flexibility to organize and adapt a tailored DSS model (or existing modular subroutines) according to the dynamic needs of a disaster. For this purpose, the existing modular subroutines of DSS models are selected and integrated to produce a dynamic integrated model focussed on a given disaster scenario. In order to facilitate the effective integration of these subroutines, it is necessary to select the appropriate modular subroutine beforehand. Therefore, subroutine selection is an important preliminary step towards model integration in developing Disaster Management Decision Support Systems (DMDSS). The ability to identify a modular subroutine for a problem is an important feature before performing model integration. Generally, decision support needs are combined, and encapsulate different requirements of decision-making in the disaster management area. Categorization of decision support needs can provide the basis for such model selection to facilitate effective and efficient decision-making in disaster management. Therefore, our focus in this paper is on developing a methodology to help identify subroutines from existing DSS models developed for disaster management on the basis of needs categorization. The problem of the formulation and execution of such modular subroutines are not addressed here. Since the focus is on the selection of the modular subroutines from the existing DMDSS models on basis of a proposed needs classification scheme.

The succession decision in Chinese–Australian family businesses : an exploratory study

This article explores the factors used to make succession choices as ethnic Chinese family business founders integrate into their host country, Australia. An empirical study of six Chinese–Australian family businesses was used to analyse what factors influence the succession decision-making process. Results show three broad factors influenced the founders’ decisions, including the aspirations and visions of the business founders, cultural and individual values shaped in the integration process, and the options that are available for succession. Findings challenge the anticipated option of intergenerational succession, with its emphasis on family-oriented collectivistic values as expectations. It provides future support for considering how the cultural value orientation (collectivistic, individualistic, or transitional) has impacted on the founder’s succession choices. Further research is required to understand how the flexible, changing, situational founder’s succession intentions are manifested among family businesses in cultural transition.

Comprehensive analysis of big data variety landscape

Big data presents a remarkable opportunity for organisations to obtain critical intelligence to drive decisions and obtain insights as never before. However, big data generates high network traffic. Moreover, the continuous growth in the variety of network traffic due to big data variety has rendered the network to be one of the key big data challenges. In this article, we present a comprehensive analysis of big data variety and its adverse effects on the network performance. We present taxonomy of big data variety and discuss various dimensions of the big data variety features. We also discuss how the features influence the interconnection network requirements. Finally, we discuss some of the challenges each big data variety dimension presents and possible approach to address them.

Decision-making on birth choices following a caesarean delivery in Taiwan

 A qualitative research aimed to explore decision-making on birth choices following a caesarean delivery in Taiwan. Safety and risk management were the major influences for both Taiwanese women’s and obstetricians’ decisions. Biased information provision regarding birth options and over-medicalisation of the birth environment contributed to women seeking repeat caesarean delivery.

A secure cloud computing based framework for big data information management of smart grid

Smart grid is a technological innovation that improves efficiency, reliability, economics, and sustainability of electricity services. It plays a crucial role in modern energy infrastructure. The main challenges of smart grids, however, are how to manage different types of front-end intelligent devices such as power assets and smart meters efficiently; and how to process a huge amount of data received from these devices. Cloud computing, a technology that provides computational resources on demands, is a good candidate to address these challenges since it has several good properties such as energy saving, cost saving, agility, scalability, and flexibility. In this paper, we propose a secure cloud computing based framework for big data information management in smart grids, which we call 'Smart-Frame.' The main idea of our framework is to build a hierarchical structure of cloud computing centers to provide different types of computing services for information management and big data analysis. In addition to this structural framework, we present a security solution based on identity-based encryption, signature and proxy re-encryption to address critical security issues of the proposed framework.

Improving waste management in construction projects: an Australian study

Construction waste generation has been identified as one of the major issues in the construction industry due to its direct impacts on the environment as well as the efficiency of the construction industry. As the industry cannot continue to practice if the environmental resources on which it depends are depleted, the significance of waste management needs to be understood in order to encourage stakeholders to achieve related goals. Therefore, this research aims to determine effective approaches to eliminate and/or minimise waste generation in construction projects. Mixed methods were adopted by combining qualitative and quantitative research approaches. Interviews and a questionnaire survey were conducted as the primary data collection methods. The findings reveal twenty six critical solutions for waste management. Five factors of solutions for waste management were extracted from the exploratory factor analysis. These factors were: team building and supervision; strategic guidelines in waste management; proper design and documentation; innovation in waste management decisions; and lifecycle management. The evidence from this study suggests that both technologies and attitudinal approaches require improvement to eliminate/minimise waste generation in construction projects. Similarly, attention should be paid to being mindful of the environmental effects of waste generation and avoiding waste generation as early as possible in construction projects.

Inclusion, organisational justice and employee well-being

Purpose: The purpose of this paper is to examine the relationship between employee perceived well-being and the four dimensions of organisational justice, namely, procedural, distributive, interpersonal and informational justice, and how dimensions of organisational justice affect employee well-being in the Australian tourism industry. Design/methodology/approach: The sample is selected from employees who work in the tourism industry in Australia, and the survey was conducted online (n=121). Factor analysis is used to identify key items related to perceived organisational justice, followed by multiple regression analysis to assess the magnitude and strength of impacts of different dimensions of organisational justice on employee well-being. Findings: The results support the established view that organisational justice is associated with employee well-being. Specifically, informational justice has the strongest influence on tourism employee well-being, followed by procedural justice, interpersonal justice and distributive justice. Research limitations/implications: The authors acknowledge key limitations in the study such as a relatively small sample size and gender imbalance in the sample. Practical implications: The authors provide strategies for managers to increase levels of organisational justice in the tourism sector such as workgroup interactions, a consultation process, team culture and social support. Originality/value: This study builds on limited literature in the area of inclusion and organisational justice in tourism organisations. The study provides a new path to effective organisational management within the context of a diverse workforce, adding to the current debate on which dimensions of organisational justice contribute to improving employee well-being.

Attending to risk in sequential sampling plans

Researchers typically tackle questions by constructing powerful, highlyreplicated sampling protocols or experimental designs. Such approaches often demand large samples sizes and are usually only conducted on a once-off basis. In contrast, many industries need to continually monitor phenomena such as equipment reliability, water quality, or the abundance of a pest. In such instances, costs and time inherent in sampling preclude the use of highlyintensive methods. Ideally, one wants to collect the absolute minimum number of samples needed to make an appropriate decision. Sequential sampling, wherein the sample size is a function of the results of the sampling process itself, offers a practicable solution. But smaller sample sizes equate to less knowledge about the population, and thus an increased risk of making an incorrect management decision. There are various statistical techniques to account for and measure risk in sequential sampling plans. We illustrate these methods and assess them using examples relating to the management of arthropod pests in commercial crops, but they can be applied to any situation where sequential sampling is used.

RQF publication quality measures: methodoligical issues

The Research Quality Framework uses Thomson-ISI citation benchmarks as its main set of objective measures of research quality. The Thomson-ISI measures rely on identifying a core set of journals in which the major publications for a discipline are to be found. The core for a discipline is determined by applying a nontransparent process that is partly based on Bradford’s Law (1934). Yet Bradford was not seeking measures about quality of publications or journals. How valid then is it to base measures of publication quality on Bradford’s Law? We explore this by returning to Bradford’s Law and subsequent related research asking ‘what is Bradford’s Law really about?’ We go further, and ask ‘does Bradford’s Law apply in Information Systems?’ We use data from John Lamp’s internationally respected Index of Information Systems Journals to explore the latter question. We have found that Information Systems may have a core of journals only a subset of which is also in the list of Thomson-ISI journals. There remain many unanswered questions about the RQF metrics based on Thomson-ISI and their applicability to information systems.

Conflict resolution and policy making mediation in the Mekong River Basin

The Mekong River serves China, Myanmar, Thailand, Laos, Cambodia and Vietnam covering an area of approximately 795, 000 square kilometres and the Mekong River basin is a delicate eco-system rich in natural resources and bio-diversity. Competing demands for increasingly scarce supplies of water, the reciprocal impacts of land and water uses and inadequate governance arrangements have given rise to conflicts that has to be resolved by policy making to facilitate a process, whereby the main principles adopted in the Mekong River Agreement can be implemented.