The diversity management approach to equal employment opportunity in Australian organisations

This article assesses the 'Managing Diversity' (MD) approach in Australia, examining its drivers, discussing its relationship to legislation designed to promote equity, and examining it as a set of management practices. It has been plausibly argued, on efficiency grounds, that responsibility for achieving equality objectives must be shifted to organisations as this links contextual conditions to organisational processes. However, even where there is some prescription and guidance such as that provided by Australian Equal Employment Opportunity (EEO) legislation targeted specifically to women employees, both practice and outcomes are variable. This is even more the case with MD where there are no guiding principles or legislative support. The article examines the best practice EEO and MD programs of Australian organisations to demonstrate the approaches and programs that are being developed at the workplace and to highlight the limitations of the 'business case' approach underlying such programs.

Future-proofing : the academic library’s role in e-research support

Purpose – The paper describes a project created to enhance e-research support activities within an Australian university, based on environmental scanning of e-research activities and funding both nationally and internationally. Participation by the university library is also described.----- Design/methodology/approach – The paper uses a case study that describes the stages of a project undertaken to develop an academic library’s capacity to offer e-research support to its institution’s research community.----- Findings – While the outcomes of the project have been successfully achieved, the work needs to be continued and eventually mainstreamed as core business in order to keep pace with developments in e-research. The continual skilling up of the university’s researchers and research support staff in e-research activities is imperative in reaching the goal of becoming a highly competitive research institution.----- Research limitations/implications – Although a single case study, the work has been contextualised within the national research agenda.----- Practical implications – The paper provides a project model that can adapted within an academic library without external or specialist skills. It is also scalable and can be applied at a divisional or broader level.----- Originality/value – The paper highlights the drivers for research investment in Australia and provides a model of how building e-research support activities can leverage this investment and contribute towards successful research activity.

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.

The role of U.S. timberland in real estate portfolios

Timberland is seen as a long-term investment which has recently received increased institutional investor attention in many countries and potentially provides added value in a mixed-asset portfolio. Using the National Council of Real Estate Investment Fiduciaries (NCREIF) timberland series, this paper analyses the risk-adjusted performance and portfolio diversification benefits of timberland in the United States over the period of 1987-2007. U.S. timberland is seen to have been a strongly performed asset class with significant portfolio diversification benefits over this period; with a significant portfolio role separate to that of real estate. However, recent years have seen reduced risk-adjusted returns, with some loss of portfolio diversification benefits of timberland with stocks and real estate. Global drivers are likely to see increased future demand for timberland investment.

Service driven asset management

Local governments are service driven rather than asset driven. Understanding this distinction is critical to ensuring that community needs are appropriately addressed. Translating community needs and desires into infrastructure is a complex yet little understood process. In this paper, we look at two case studies that explore the interface between service outcomes and the specification of performance requirements for the assets. The two case studies we look at are: a public health issue resulting from inadequate public amenities in a beach resort and the prioritisation of maintenance work in a world of increasing service demands and declining funding. The case studies all use the same investment logic mapping framework to establish clear drivers as to the problem that councils are responding to in delivering their services. The key to the framework is the separation of concern between service management and asset management.

Customer-oriented deviance (COD) : a conceptualisation, development and validation of a behavioural measure

Frontline employee behaviours are recognised as vital for achieving a competitive advantage for service organisations. The services marketing literature has comprehensively examined ways to improve frontline employee behaviours in service delivery and recovery. However, limited attention has been paid to frontline employee behaviours that favour customers in ways that go against organisational norms or rules. This study examines these behaviours by introducing a behavioural concept of Customer-Oriented Deviance (COD). COD is defined as, “frontline employees exhibiting extra-role behaviours that they perceive to defy existing expectations or prescribed rules of higher authority through service adaptation, communication and use of resources to benefit customers during interpersonal service encounters.” This thesis develops a COD measure and examines the key determinants of these behaviours from a frontline employee perspective. Existing research on similar behaviours that has originated in the positive deviance and pro-social behaviour domains has limitations and is considered inadequate to examine COD in the services context. The absence of a well-developed body of knowledge on non-conforming service behaviours has implications for both theory and practice. The provision of ‘special favours’ increases customer satisfaction but the over-servicing of customers is also counterproductive for the service delivery and costly for the organisation. Despite these implications of non-conforming service behaviours, there is little understanding about the nature of these behaviours and its key drivers. This research builds on inadequacies in prior research on positive deviance, pro-social and pro-customer literature to develop the theoretical foundation of COD. The concept of positive deviance which has predominantly been used to study organisational behaviours is applied within a services marketing setting. Further, it addresses previous limitations in pro-social and pro-customer behavioural literature that has examined limited forms of behaviours with no clear understanding on the nature of these behaviours. Building upon these literature streams, this research adopts a holistic approach towards the conceptualisation of COD. It addresses previous shortcomings in the literature by providing a well bounded definition, developing a psychometrically sound measure of COD and a conceptually well-founded model of COD. The concept of COD was examined across three separate studies and based on the theoretical foundations of role theory and social identity theory. Study 1 was exploratory and based on in-depth interviews using the Critical Incident Technique (CIT). The aim of Study 1 was to understand the nature of COD and qualitatively identify its key drivers. Thematic analysis was conducted to analyse the data and the two potential dimensions of COD behaviours of Deviant Service Adaptation (DSA) and Deviant Service Communication (DSC) were revealed in the analysis. In addition, themes representing the potential influences of COD were broadly classified as individual factors, situational factors, and organisational factors. Study 2 was a scale development procedure that involved the generation and purification of items for the measure based on two student samples working in customer service roles (Pilot sample, N=278; Initial validation sample, N=231). The results for the reliability and Exploratory Factor Analyses (EFA) on the pilot sample suggested the scale had poor psychometric properties. As a result, major revisions were made in terms of item wordings and new items were developed based on the literature to reflect a new dimension, Deviant Use of Resources (DUR). The revised items were tested on the initial validation sample with the EFA analysis suggesting a four-factor structure of COD. The aim of Study 3 was to further purify the COD measure and test for nomological validity based on its theoretical relationships with key antecedents and similar constructs (key correlates). The theoretical model of COD consisting of nine hypotheses was tested on a retail and hospitality sample of frontline employees (Retail N=311; Hospitality N=305) of a market research panel using an online survey. The data was analysed using Structural Equation Modelling (SEM). The results provided support for a re-specified second-order three-factor model of COD which consists of 11 items. Overall, the COD measure was found to be reliable and valid, demonstrating convergent validity, discriminant validity and marginal partial invariance for the factor loadings. The results showed support for nomological validity, although the antecedents had differing impact on COD across samples. Specifically, empathy and perspective-taking, role conflict, and job autonomy significantly influenced COD in the retail sample, whereas empathy and perspective-taking, risk-taking propensity and role conflict were significant predictors in the hospitality sample. In addition, customer orientation-selling orientation, the altruistic dimension of organisational citizenship behaviours, workplace deviance, and social desirability responding were found to correlate with COD. This research makes several contributions to theory. First, the findings of this thesis extend the literature on positive deviance, pro-social and pro-customer behaviours. Second, the research provides an empirically tested model which describes the antecedents of COD. Third, this research contributes by providing a reliable and valid measure of COD. Finally, the research investigates the differential effects of the key antecedents in different service sectors on COD. The research findings also contribute to services marketing practice. Based on the research findings, service practitioners can better understand the phenomenon of COD and utilise the measurement tool to calibrate COD levels within their organisations. Knowledge on the key determinants of COD will help improve recruitment and training programs and drive internal initiatives within the firm.

Texting while driving : psychosocial influences on young people’s texting intentions and behaviour

Despite the dangers and illegality, there is a continued prevalence of texting while driving amongst young Australian drivers. The present study tested an extended theory of planned behaviour (TPB) to predict young drivers��� (17 to 24 years) intentions to [1] send and [2] read text messages while driving. Participants (N = 169 university students) completed measures of attitudes, subjective norm, perceived behavioural control, intentions, and the additional social influence measures of group norm and moral norm. One week later, participants reported on the number of texts sent and read while driving in the previous week. Attitude predicted intentions to both send and read texts while driving, and subjective norm and perceived behavioural control determined sending, but not reading, intentions. Further, intention, but not perceptions of control, predicted both texting behaviours 1 week later. In addition, both group norm and moral norm added predictive ability to the model. These findings provide support for the TPB in understanding students’ decisions to text while driving as well as the inclusion of additional normative influences within this context, suggesting that a multi-strategy approach is likely to be useful in attempts to reduce the incidence of these risky driving behaviours.

Motivational misalignment on an iconic infrastructure project

Aligning the motivation of contractors and consultants to perform better than ‘business-as-usual’ (BAU) on a construction project is a complex undertaking and the costs of failure are high as misalignment can compromise project outcomes. Despite the potential benefits of effective alignment, there is still little information about optimally designing procurement approaches that promote motivation towards ‘above BAU’ goals. The paper contributes to this knowledge gap by examining the negative drivers of motivation in a major construction project that, despite a wide range of performance enhancing incentives, failed to exceed BAU performance. The paper provides a case study of an iconic infrastructure project undertaken in Australia between 2002 and 2004. It is shown that incentives provided to contractors and consultants to achieve above BAU performance can be compromised by a range of negative motivation drivers including: • inequitable contractual risk allocation; • late involvement of key stakeholders; • inconsistency between contract intentions and relationship intentions; • inadequate price negotiation; • inconsistency between the project performance goals and incentive goals; •unfair and inflexible incentive performance measurement processes. Future quantitative research is planned to determine the generalisability of these results.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Lip detection for audio-visual speech recognition in-car environment

Acoustically, car cabins are extremely noisy and as a consequence audio-only, in-car voice recognition systems perform poorly. As the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem by using audio visual automatic speech recognition (AVASR). However, implementing AVASR requires a system being able to accurately locate and track the drivers face and lip area in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using the AVICAR [1] in-car database, we show that the Viola- Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose for audio-visual speech recognition system.

Driving performance on monotonous roads

Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers��� crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

Small firm growth

We review and discuss the literature on small firm growth with an intention to provide a useful vantage point for new research studies regarding this important phenomenon. We first discuss conceptual and methodological issues that represent critical choices for those who research growth and which make it challenging to compare results from previous studies. The substantial review of past research is organized into four sections representing two smaller and two larger literatures. The first of the latter focuses on internal and external drivers of small firm growth. Here we find that much has been learnt and that many valuable generalizations can be made. However, we also conclude that more research of the same kind is unlikely to yield much. While interactive and non-linear effects may be worth pursuing it is unlikely that any new and important growth drivers or strong, linear main effects would be found. The second large literature deals with organizational life-cycles or stages of development. While deservedly criticized for unwarranted determinism and weak empirics this type of approach addresses problems of high practical and also theoretical relevance, and should not be shunned by researchers. We argue that with a change in the fundamental assumptions and improved empirical design, research on the organizational and managerial consequences of growth is an important line of inquiry. With this, we overlap with one of the smaller literatures, namely studies focusing on the effects of growth. We argue that studies too often assume that growth equals success. We advocate instead the use of growth as an intermediary variable that influences more fundamental goals in ways that should be carefully examined rather than assumed. The second small literature distinguishes between different modes or forms of growth, including, e.g., organic vs. acquisition-based growth, and international expansion. We note that modes of growth is an important topic that has been under studied in the growth literature, whereas in other branches of research aspects of it may have been studied intensely, but not primarily from a growth perspective. In the final section we elaborate on ways forward for research on small firm growth. We point at rich opportunities for researchers who look beyond drivers of growth, where growth is viewed as a homogenous phenomenon assumed to unambiguously reflect success, and instead focus on growth as a process and a multi-dimensional phenomenon, as well as on how growth relates to more fundamental outcomes.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.