Procurement selection in the public sector : a tale of two states.

The decision as to which procurement system to adopt is a complex and challenging task for clients of construction projects. Despite a plethora of tools and techniques available for selecting a procurement method, clients are still uncertain about what method to adopt for a given construction project to achieve success. This paper examines ‘how and why’ procurement methods are selected by public sector clients in Queensland (QLD) and Western Australia (WA). Findings from workshops with senior managers in procurement selection revealed that traditional lump sum methods (TLS) are preferred even though alternative forms could be better suited for a given project. Participants of the workshops agreed that alternative procurement forms should be considered for projects but an embedded culture of uncertainty avoidance meant the selection of TLS methods. It was perceived that only a limited number of contractors operating in the marketplace have the resources and experience to deliver projects using the non-traditional methods.

Can governments use their construction contracts to improve training outcomes?

This paper explores the likely efficacy of government agencies using their contracting relationships with private firms to affect training outcomes in the construction industry. Specifically, it reports on the results of a study of two training policies of theWestern Australian government. Empirical data is drawn from the government’s Tender Registration System between 1997 and 2006. The main finding of the quantitative analysis is that in the absence of strong industry commitment to policy objectives, the contracting approach is likely to result in high levels of avoidance activity and generate very few benefits. The results of a qualitative investigation also support these findings.

The Melbourne Decision-Making Questionnaire : an instrument for measuring patterns for coping with decisional conflict

A study was conducted to examine the factorial validity of the Flinders Decision Making Questionnaire (Mann, 1982), a 31-item self-report inventory designed to measure tendencies to use three major coping patterns identified in the conflict theory of decision making (Janis and Mann, 1977): vigilance, hypervigilance, and defensive avoidance (procrastination, buck-passing, and rationalization). A sample of 2051 university students, comprising samples from Australia (n=262), New Zealand (n=260), the USA (n=475), Japan (n=359), Hong Kong (n=281) and Taiwan (n=414) was administered the DMQ. Factorial validity of the instrument was tested by confirmatory factor analysis with LISREL. Five different substantive models, representing different structural relationships between the decision-coping patterns had unsatisfactory fit to the data and could not be validated. A shortened instrument, containing 22 items, yielded a revised model comprising four identifiable factors-vigilance, hypervigilance, buck-passing, and procrastination. The revised model had adequate fit with data for each country sample and for the total sample, and was confirmed. It is recommended that the 22-item instrument, named the Melbourne DMQ, replace the Flinders DMQ for measurement of decision-coping patterns.

Decision-making style and self-concept

The Flinders Decision-Making Questionnaire (FDMQ) (Mann, 1982), which measures three decision-making styles and decision-making self-esteem, and the Self-Description Questionnaire III (SDQ HI) (Marsh & O'Neill, 1984), which measures 13 facets of self-concept; were administered to 475 university students to investigate some of the tenets of Janis and Mann's (1976, 1977) conflict model of decision-making and to further investigate the influence of self-concept on decision-making behaviours. The findings empirically validated Janis and Mann's (1977) link between decision-making self-esteem and decision-making style. Modest relationships, in the predicted direction, were found between decision-making self-esteem and the three decision-making styles (Vigilance, Defensive Avoidance, and Hypervigilance). In addition, specific facets of self-concept (General, Verbal, Academic, Honesty/Reliability and Problem-Solving Self Concepts) were related to self-reported decision-making behaviours.

Validation of the Flinders decision : making questionnaire in course decision making by students

The Flinders Decision Making Questionnaire (DMQ; Mann, 1982) was designed to measure decision making coping patterns identified by Janis and Mann (1977). The validity of four DMQ Scales (vigilance, defensive avoidance, hypervigilance, and decision self-esteem) were tested as predictors of students' course and career decision making. Students administered the DMQ scales were also measured on independence of choice, satisfaction, and planfulness relating to their university course and on planfulness and options relating to their future employment. Two samples were studied. In study 1, 40 students residing in a university college were the subjects. In Study 2, 42 second-year students who completed the DMQ one year earlier constituted the subjects. Modest but significant correlations were found in both samples between DMQ scores and measures of course and career decision making. The findings lend support to the validity of the DMQ as an instrument for measuring decision making behaviour.

Adventures in cyberformance

This thesis examines the new theatrical form of cyberformance (live performance by remote players using internet technologies) and contextualises it within the broader fields of networked performance, digital performance and theatre. Poststructuralist theories that contest the binary distinction between reality and representation provide the analytical foundation for the thesis. A critical reflexive methodological approach is undertaken in order to highlight three themes. First, the essential qualities and criteria of cyberformance are identified, and illustrated with examples from the early 1990s to the present day. Second, two cyberformance groups – the Plaintext Players and Avatar Body Collision – and UpStage, a purpose-built application for cyberformance, are examined in more detailed case studies. Third, the specifics of the cyberformance audience are explored and commonalities are identified between theatre and online culture. In conclusion, this thesis suggests that theatre and the internet have much to offer each other in this current global state of transition, and that cyberformance offers one means by which to facilitate the incorporation of new technologies into our lives.

The foraging behaviour of the Black rat (Rattus rattus) within Australian macadamia orchards

The black rat (Rattus rattus) has been shown to be the primary species responsible for causing significant crop losses within the Australian macadamia industry. This species success within macadamia orchards is directly related to the flexibility expressed in its foraging behaviour. In this paper a conceptual foraging model is presented which proposes that the utilisation of resources by rodents within various components of the system is related not only to their relative abundance, but also to predator avoidance behaviour. Nut removal from high predation risk habitats during periods of low resource abundance in low risk compartments of the system is considered an essential behaviour that allows high rodent densities to be maintained throughout the year.

Applying Stafford and Warr’s Reconceptualization of Deterrence Theory to drug driving : can it predict those likely to offend?

In December 2007, random roadside drug testing commenced in Queensland, Australia. Subsequently, the aim of this study was to explore the preliminary impact of Queensland’s drug driving legislation and enforcement techniques by applying Stafford and Warr’s [Stafford, M. C., & Warr, M. (1993). A reconceptualization of general and specific deterrence. Journal of Research in Crime and Delinquency, 30, 123-135] reconceptualization of deterrence theory. Completing a comprehensive drug driving questionnaire were 899 members of the public, university students, and individuals referred to a drug diversion program. Of note was that approximately a fifth of participants reported drug driving in the past six months. Additionally, the analysis indicated that punishment avoidance and vicarious punishment avoidance were predictors of the propensity to drug drive in the future. In contrast, there were indications that knowing of others apprehended for drug driving was not a sufficient deterrent. Sustained testing and publicity of the legislation and countermeasure appears needed to increase the deterrent impact for drug driving.

"There's no way in hell I would pull up" : Deterrent and other effects of vehicle impoundment laws for hooning

Traffic law enforcement is based on deterrence principles, whereby drivers control their behaviour in order to avoid an undesirable sanction. For “hooning”-related driving behaviours in Queensland, the driver’s vehicle can be impounded for 48 hours, 3 months, or permanently depending on the number of previous hooning offences. It is assumed that the threat of losing something of value, their vehicle, will discourage drivers from hooning. While official data shows that the rate of repeat offending is low, an in-depth understanding of the deterrent effects of these laws should involve qualitative research with targeted drivers. A sample of 22 drivers who reported engaging in hooning behaviours participated in focus group discussions about the vehicle impoundment laws as applied to hooning offences in Queensland. The findings suggested that deterrence theory alone cannot fully explain hooning behaviour, as participants reported hooning frequently, and intended to continue doing so, despite reporting that it is likely that they will be caught, and perceiving the vehicle impoundment laws to be extremely severe. The punishment avoidance aspect of deterrence theory appears important, as well as factors over and above legal issues, particularly social influences. A concerning finding was drivers’ willingness to flee from police in order to avoid losing their vehicle permanently for a third offence, despite acknowledging risks to their own safety and that of others. This paper discusses the study findings in terms of the implications for future research directions, enforcement practices and policy development for hooning and other traffic offences for which vehicle impoundment is applied.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Drivers' and cyclists' experiences of sharing the road : incidents, attitudes and perceptions of visibility

This study explored the beliefs and attitudes of cyclists and drivers regarding cyclist visibility, use of visibility aids and crashes involving cyclists and motorists. Data are presented for 1460 participants (622 drivers and 838 cyclists) and demonstrate that there are high rates of cyclist–vehicle crashes, many of which were reported to be due to the driver not seeing the cyclist in time to avoid a collision. A divergence in attitudes was also apparent in terms of attribution of responsibility in cyclist–vehicle conflicts on the road. While the use of visibility aids was advocated by cyclists, this was not reflected in self-reported wearing patterns, and cyclists reported that the distance at which they would be first recognised by a driver was twice that estimated by the drivers. Collectively, these results suggest that interventions should target cyclists’ use of visibility aids, which is less than optimal in this population, as well as re-educating both groups regarding visibility issues.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

The speed paradox : the misalignment between driver attitudes and speeding behaviour

This paper reports on a study investigating preferred driving speeds and frequency of speeding of 320 Queensland drivers. Despite growing community concern about speeding and extensive research linking it to road trauma, speeding remains a pervasive, and arguably, socially acceptable behaviour. This presents an apparent paradox regarding the mismatch between beliefs and behaviours, and highlights the necessity to better understand the factors contributing to speeding. Utilising self-reported behaviour and attitudinal measures, results of this study support the notion of a speed paradox. Two thirds of participants agreed that exceeding the limit is not worth the risks nor is it okay to exceed the posted limit. Despite this, more than half (58.4%) of the participants reported a preference to exceed the 100km/hour speed limit, with one third preferring to do so by 10 to 20 km/hour. Further, mean preferred driving speeds on both urban and open roads suggest a perceived enforcement tolerance of 10%, suggesting that posted limits have limited direct influence on speed choice. Factors that significantly predicted the frequency of speeding included: exposure to role models who speed; favourable attitudes to speeding; experiences of punishment avoidance; and the perceived certainty of punishment for speeding. These findings have important policy implications, particularly relating to the use of enforcement tolerances.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.