Extending life-cycle costing (LCC) analysis for sustainability considerations in road infrastructure projects

Sustainable development is about making societal investments. These investments should be in synchronization with the natural environment, trends of social development, as well as organisational and local economies over a long time span. Traditionally in the eyes of clients, project development will need to produce the required profit margins, with some degrees of consideration for other impacts. This is being changed as all citizens of our society are becoming more aware of concepts and challenges such as the climate change, greenhouse footprints, and social dimensions of sustainability, and will in turn demand answers to these issues in built facilities. A large number of R&D projects have focused on the technical advancement and environmental assessment of products and built facilities. It is equally important address the cost/benefit issue, as developers in the world would not want to loose money by investing in built assets. For infrastructure projects, due to its significant cost of development and lengthy delivery time, presenting the full money story of going green is of vital importance. Traditional views of life-cycle costing tend to focus on the pure economics of a construction project. Sustainability concepts are not broadly integrated with the current LCCA in the construction sector. To rectify this problem, this paper reports on the progress to date of developing and extending contemporary LCCA models in the evaluation of road infrastructure sustainability. The suggested new model development is based on sustainability indicators identified through previous research, and incorporating industry verified cost elements of sustainability measures. The on-going project aims to design and a working model for sustainability life-cycle costing analysis for this type of infrastructure projects.

Campylobacter jejuni and campylobacter coli genotyping by high-resolution melting analysis of a flaA fragment

The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaAHRManalysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.

An analysis of cyclists crashes to identify ITS-based intervention

Cycling provides a number of health and environmental benefits. However, cyclists are more likely to suffer serious injury or be killed in traffic accidents than car drivers and the estimated cost of crashes in Australia is $1.25AU billion per year. Current interventions to reduce bicycle crashes include compulsory helmet use, media campaigns, and the provision of cycling lanes, as well as road user education and training. It is difficult to assess the effectiveness of current interventions as there is no accurate measure of cyclist exposure in South East Queensland (SEQ). This paper analyses cyclist crash characteristics in Queensland with the view to identifying appropriate Intelligent Transport Systems (ITS) based intervention to reduce cyclist injury and death. The inappropriateness of some ITS interventions to improve cyclist safety is highlighted and a set of ITS interventions are identified, based on Queensland crash data 2002-2006.

Power system stability analysis based on descriptive study of electrical indices

In a power network, when a propagation energy wave caused by a disturbance hits a weak link, a reflection is appeared and some of energy is transferred across the link. In this work, an analytical descriptive methodology is proposed to study the dynamical stability of a large scale power system. For this purpose, the measured electrical indices (angle, or voltage/frequency) following a fault in different points among the network are used, and the behaviors of the propagated waves through the lines, nodes and buses are studied. This work addresses a new tool for power system stability analysis based on a descriptive study of electrical measurements. The proposed methodology is also useful to detect the contingency condition and synthesis of an effective emergency control scheme.

A regulatory analysis of international climate change regulation

The political challenges impeding the negotiation of a comprehensive multilateral agreement on international climate change have received a great deal of attention. A question that has gone somewhat overlooked is what essential components an effective regulatory scheme to reduce greenhouse gas emissions should contain. The objective of this article is to examine the regulatory architecture of current international arrangements relating to global climate change regulation. A systematic analysis of the structure, substantive composition, and administrative characteristics of the UNFCCC and Kyoto Protocol is undertaken. The analytical standard against which the agreements are examined is whether current international regulatory arrangements satisfy the basic requirements of regulatory coherence. The analysis identifies how the present scheme consists of a complex institutional structure that lacks a substantive regulatory core. The implications of the absence of functional and effective mechanisms to govern greenhouse gas emission reductions are considered in relation to the principles of good regulatory design. This, in turn, provides useful insights into how a better regulatory scheme might be designed.

Strategic information systems research : an archival analysis

The Journal of Strategic Information Systems (JSIS) has been an international outlet for Information Systems research that focuses on strategic issues since 1991. This paper reports on an analysis of the research published in JSIS to date. The paper presents a preliminary classification system for research topics related to Strategic Information Systems into which all 316 JSIS research papers as at end 2009 are classified. Discussion on changing emphases in topics over time is provided, in the context of the editorial philosophy of the journal. The paper seeks to stimulate discussion on future directions for research in Strategic Information Systems.

Demographic category membership and leadership in small groups : a social identity analysis

Developing the social identity theory of leadership (e.g., [Hogg, M. A. (2001). A social identity theory of leadership. Personality and Social Psychology Review, 5, 184–200]), an experiment (N=257) tested the hypothesis that as group members identify more strongly with their group (salience) their evaluations of leadership effectiveness become more strongly influenced by the extent to which their demographic stereotype-based impressions of their leader match the norm of the group (prototypicality). Participants, with more or less traditional gender attitudes (orientation), were members, under high or low group salience conditions (salience), of non-interactive laboratory groups that had “instrumental” or “expressive” group norms (norm), and a male or female leader (leader gender). As predicted, these four variables interacted significantly to affect perceptions of leadership effectiveness. Reconfiguration of the eight conditions formed by orientation, norm and leader gender produced a single prototypicality variable. Irrespective of participant gender, prototypical leaders were considered more effective in high then low salience groups, and in high salience groups prototypical leaders were more effective than less prototypical leaders. Alternative explanations based on status characteristics and role incongruity theory do not account well for the findings. Implications of these results for the glass ceiling effect and for a wider social identity analysis of the impact of demographic group membership on leadership in small groups are discussed.

Critical discourse analysis and political economy of communication : understanding the new corporate order

This article uses critical discourse analysis to analyse material shifts in the political economy of communications. It examines texts of major corporations to describe four key changes in political economy: (1) the separation of ownership from control; (2) the separation of business from industry; (3) the separation of accountability from responsibility; and (4) the subjugation of ‘going concerns’ by overriding concerns. The authors argue that this amounts to a political economic shift from traditional concepts of ‘capitalism’ to a new ‘corporatism’ in which the relationships between public and private, state and individual interests have become redefined and obscured through new discourse strategies. They conclude that the present financial and regulatory ‘crisis’ cannot be adequately resolved without a new analytic framework for examining the relationships between corporation, discourse and political economy.

What shapes player performance in soccer? Empirical findings from a panel analysis

In this article, we investigate the pay-performance relationship of soccer players using individual data from eight seasons of the German soccer league Bundesliga. We find a nonlinear pay-performance relationship, indicating that salary does indeed affect individual performance. The results further show that player performance is affected not only by absolute income level but also by relative income position. An additional analysis of the performance impact of team effects provides evidence of a direct impact of team-mate attributes on individual player performance.

An analysis of the determinants of job satisfaction when individuals' baseline satisfaction levels may differ.

A growing literature seeks to explain differences in individuals' self-reported satisfaction with their jobs. The evidence so far has mainly been based on cross-sectional data and when panel data have been used, individual unobserved heterogeneity has been modelled as an ordered probit model with random effects. This article makes use of longitudinal data for Denmark, taken from the waves 1995-1999 of the European Community Household Panel, and estimates fixed effects ordered logit models using the estimation methods proposed by Ferrer-i-Carbonel and Frijters (2004) and Das and van Soest (1999). For comparison and testing purposes a random effects ordered probit is also estimated. Estimations are carried out separately on the samples of men and women for individuals' overall satisfaction with the jobs they hold. We find that using the fixed effects approach (that clearly rejects the random effects specification), considerably reduces the number of key explanatory variables. The impact of central economic factors is the same as in previous studies, though. Moreover, the determinants of job satisfaction differ considerably between the genders, in particular once individual fixed effects are allowed for.

Thermal analysis and hot stage Raman spectroscopy of the basic copper arsenate mineral : euchroite

The thermal analysis of euchroite shows two mass loss steps in the temperature range 100 to 105°C and 185 to 205°C. These mass loss steps are attributed to dehydration and dehydroxylation of the mineral. Hot stage Raman spectroscopy (HSRS) has been used to study the thermal stability of the mineral euchroite, a mineral involved in a complex set of equilibria between the copper hydroxy arsenates: euchroite Cu2(AsO4)(OH).3H2O → olivenite Cu2(AsO4)(OH) → strashimirite Cu8(AsO4)4(OH)4.5H2O → arhbarite Cu2Mg(AsO4)(OH)3. Hot stage Raman spectroscopy inolves the collection of Raman spectra as a function of the temperature. HSRS shows that the mineral euchroite decomposes between 125 and 175 °C with the loss of water. At 125 °C, Raman bands are observed at 858 cm-1 assigned to the ν1 AsO43- symmetric stretching vibration and 801, 822 and 871 cm-1 assigned to the ν3 AsO43- (A1) antisymmetric stretching vibration. A distinct band shift is observed upon heating to 275 °C. At 275 °C the four Raman bands are resolved at 762, 810, 837 and 862 cm-1. Further heating results in the diminution of the intensity in the Raman spectra and this is attributed to sublimation of the arsenate mineral. Hot stage Raman spectroscopy is most useful technique for studying the thermal stability of minerals especially when only very small amounts of mineral are available.

Thermogravimetric analysis and hot stage Raman spectroscopy of cubic indium hydroxide

The transition of cubic indium hydroxide to cubic indium oxide has been studied by thermogravimetric analysis complimented with hot stage Raman spectroscopy. Thermal analysis shows the transition of In(OH)3 to In2O3 occurs at 219°C. The structure and morphology of In(OH)3 synthesised using a soft chemical route at low temperatures was confirmed by X-ray diffraction and scanning electron microscopy. A topotactical relationship exists between the micro/nano-cubes of In(OH)3 and In2O3. The Raman spectrum of In(OH)3 is characterised by an intense sharp band at 309 cm-1 attributed to ν1 In-O symmetric stretching mode, bands at 1137 and 1155 cm-1 attributed to In-OH δ deformation modes, bands at 3083, 3215, 3123 and 3262 cm-1 assigned to the OH stretching vibrations. Upon thermal treatment of In(OH)3 new Raman bands are observed at 125, 295, 488 and 615 cm-1 attributed to In2O3. Changes in the structure of In(OH)3 with thermal treatment is readily followed by hot stage Raman spectroscopy.

Thermal analysis of synthetic reevesite and cobalt substituted reevesite (Ni,Co)6Fe2(OH)16(CO3)•4H2O

The mineral reevesite and the cobalt substituted reevesite have been synthesised. The d(003) spacings of the minerals ranged from 7.54 to 7.95 Å. The maximum d(003) value occurred at around Ni:Co 0.4:0.6. This maximum in interlayer distance is proposed to be due to a greater number of carbonate anions and water molecules intercalated into the structure. The stability of the reevesite and cobalt doped reevesite was determined by thermogravimetric analysis. The maximum temperature of the reevesite occurs for the unsubstituted reevesite and is around 220°C. The effect of cobalt substitution results in a decrease in thermal stability of the reevesites. Four thermal decomposition steps are observed and are attributed to dehydration, dehydroxylation and decarbonation, decomposition of the formed carbonate and oxygen loss at ~807 °C. A mechanism for the thermal decomposition of the reevesite and the cobalt substituted reevesite is proposed.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Inter- and intra- project knowledge transfer : analysis of knowledge transfer techniques

Many studies in the area of project management and social networks have identified the significance of project knowledge transfer within and between projects. However, only few studies have examined the intra- and inter-projects knowledge transfer activities. Knowledge in projects can be transferred via face-to-face interactions on the one hand, and via IT-based tools on the other. Although companies have allocated many resources to the IT tools, it has been found that they are not always effectively utilised, and people prefer to look for knowledge using social face-to-face interactions. This paper explores how to effectively leverage two alternative knowledge transfer techniques, face-to-face and IT-based tools to facilitate knowledge transfer and enhance knowledge creation for intra- and inter-project knowledge transfer. The paper extends the previous research on the relationships between and within teams by examining the project’s external and internal knowledge networks concurrently. Social network qualitative analysis, using a case study within a small-medium enterprise, was used to examine the knowledge transfer activities within and between projects, and to investigate knowledge transfer techniques. This paper demonstrates the significance of overlapping employees working simultaneously on two or more projects and their impact on facilitating knowledge transfer between projects within a small/medium organisation. This research is also crucial to gaining better understanding of different knowledge transfer techniques used for intra- and inter-project knowledge exchange. The research provides recommendations on how to achieve better knowledge transfer within and between projects in order to fully utilise a project’s knowledge and achieve better project performance.