Validating a model of cooperative procurement in the construction industry

Project management in the construction industry involves coordination of many tasks and individuals, affected by complexity and uncertainty, which increases the need for efficient cooperation. Procurement is crucial since it sets the basis for cooperation between clients and contractors. This is true whether the project is local, regional or global in scope. Traditionally, procurement procedures are competitive, resulting in conflicts, adversarial relationships and less desirable project results. The purpose of this paper is to propose and empirically test an alternative procurement model based on cooperative procurement procedures that facilitates cooperation between clients and contractors in construction projects. The model is based on four multi-item constructs – incentive-based compensation, limited bidding options, partner selection and cooperation. Based on a sample of 87 client organisations, the model was empirically tested and exhibited strong support, including content, nomological, convergent and discriminant validity, as well as reliability. Our findings indicate that partner selection based on task related attributes mediates the relationship between two important pre-selection processes (incentive-based compensation and limited bid invitation) and preferred outcome of cooperation. The contribution of the paper is identifying valid and reliable measurement constructs and confirming a unique sequential order for achieving cooperation. Moreover, the findings are applicable for many types of construction projects because of the similarities in the construction industry worldwide.

Parameter estimation for a phenomenological model of the cardiac action potential

The action potential (ap) of a cardiac cell is made up of a complex balance of ionic currents which flow across the cell membrane in response to electrical excitation of the cell. Biophysically detailed mathematical models of the ap have grown larger in terms of the variables and parameters required to model new findings in subcellular ionic mechanisms. The fitting of parameters to such models has seen a large degree of parameter and module re-use from earlier models. An alternative method for modelling electrically exciteable cardiac tissue is a phenomenological model, which reconstructs tissue level ap wave behaviour without subcellular details. A new parameter estimation technique to fit the morphology of the ap in a four variable phenomenological model is presented. An approximation of a nonlinear ordinary differential equation model is established that corresponds to the given phenomenological model of the cardiac ap. The parameter estimation problem is converted into a minimisation problem for the unknown parameters. A modified hybrid Nelder–Mead simplex search and particle swarm optimization is then used to solve the minimisation problem for the unknown parameters. The successful fitting of data generated from a well known biophysically detailed model is demonstrated. A successful fit to an experimental ap recording that contains both noise and experimental artefacts is also produced. The parameter estimation method’s ability to fit a complex morphology to a model with substantially more parameters than previously used is established.

Developing a model of embedding academic numeracy in university programs : a case study from nursing

This is a study of the academic numeracy of nursing students. This study develops a theoretical model for the design and delivery of university courses in academic numeracy. The following objectives are addressed: 1. To investigate nursing students' current knowledge of academic numeracy; 2. To investigate how nursing students’ knowledge and skills in academic numeracy can be enhanced using a developmental psychology framework; and 3. To utilise data derived from meeting objectives 1 and 2 to develop a theoretical model to embed academic numeracy in university programs. This study draws from Valsiner’s Human Development Theory (Valsiner, 1997, 2007). It is a quasi-experimental intervention case study (Faltis, 1997) and takes a multimethod approach using pre- and post-tests; observation notes; and semi-structured teaching sessions to document a series of microgenetic studies of student numeracy. Each microgenetic study is centered on the lived experience of students becoming more numerate. The method for this section is based on Vygotsky’s double stimulation (Valsiner, 2000a; 2007). Data collection includes interviews on students’ past experience with mathematics; their present feelings and experiences and how these present feelings and experiences are transformed. The findings from this study have provided evidence that the course developed for nursing students, underpinned by an appropriate framework, does improve academic numeracy. More specifically, students improved their content knowledge of and confidence in mathematics in areas that were directly related to their degree. The study used Valsiner’s microgenetic approach to development to trace the course as it was being taught and two students’ personal academic numeracy journeys. It highlighted particularly troublesome concepts, then outlined scaffolding and pathways used to develop understanding. This approach to academic numeracy development was summarised into a four-faceted model at the university, program, course and individual level. This model can be applied successfully to similar contexts. Thus the thesis advances both theory and practice in this under-researched and under-theorised area.

An examination of the predictors of blood donors' intentions to donate during two phases of an avian influenza outbreak

BACKGROUND: Data from prior health scares suggest that an avian influenza outbreak will impact on people’s intention to donate blood; however research exploring this is scarce. Using an augmented theory of planned behavior (TPB), incorporating threat perceptions alongside the rational decision-making components of the TPB, the current study sought to identify predictors of blood donors’ intentions to donate during two phases of an avian influenza outbreak. STUDY DESIGN AND METHODS: Blood donors (N = 172) completed an on-line survey assessing the standard TPB predictors as well as measures of threat perceptions from the health belief model (HBM; i.e., perceived susceptibility and severity). Path analyses examined the utility of the augmented TPB to predict donors’ intentions to donate during a low- and high-risk phase of an avian influenza outbreak. RESULTS: In both phases, the model provided a good fit to the data explaining 69% (low risk) and 72% (high risk) of the variance in intentions. Attitude, subjective norm, and perceived susceptibility significantly predicted donor intentions in both phases. Within the low-risk phase, gender was an additional significant predictor of intention, while in the high-risk phase, perceived behavioral control was significantly related to intentions. CONCLUSION: An augmented TPB model can be used to predict donors’ intentions to donate blood in a low-risk and a high-risk phase of an outbreak of avian influenza. As such, the results provide important insights into donors’ decision-making that can be used by blood agencies to maintain the blood supply in the context of an avian influenza outbreak.

Towards a model of dynamic capabilities in innovation-based competitive strategy : insights from project-oriented service firms

With the growing significance of services in most developed economies, there is an increased interest in the role of service innovation in service firm competitive strategy. Despite growing literature on service innovation, it remains fragmented reflecting the need for a model that captures key antecedents driving the service innovation-based competitive advantage process. Building on extant literature and using thirteen in-depth interviews with CEOs of project-oriented service firms, this paper presents a model of innovation-based competitive advantage. The emergent model suggests that entrepreneurial service firms pursuing innovation carefully select and use dynamic capabilities that enable them to achieve greater innovation and sustained competitive advantage. Our findings indicate that firms purposefully use create, extend and modify processes to build and nurture key dynamic capabilities. The paper presents a set of theoretical propositions to guide future research. Implications for theory and practice are discussed. Finally, directions for future research are outlined.

The Metapopulation Dynamics of an Infectious Disease: Tuberculosis in Possums

An SEI metapopulation model is developed for the spread of an infectious agent by migration. The model portrays two age classes on a number of patches connected by migration routes which are used as host animals mature. A feature of this model is that the basic reproduction ratio may be computed directly, using a scheme that separates topography, demography, and epidemiology. We also provide formulas for individual patch basic reproduction numbers and discuss their connection with the basic reproduction ratio for the system. The model is applied to the problem of spatial spread of bovine tuberculosis in a possum population. The temporal dynamics of infection are investigated for some generic networks of migration links, and the basic reproduction ratio is computed—its value is not greatly different from that for a homogeneous model. Three scenarios are considered for the control of bovine tuberculosis in possums where the spatial aspect is shown to be crucial for the design of disease management operations

The role of cognitive and visual abilities as predictors in the Multifactorial Model of Driving Safety

Objective The current study evaluated part of the Multifactorial Model of Driving Safety to elucidate the relative importance of cognitive function and a limited range of standard measures of visual function in relation to the Capacity to Drive Safely. Capacity to Drive Safely was operationalized using three validated screening measures for older drivers. These included an adaptation of the well validated Useful Field of View (UFOV) and two newer measures, namely a Hazard Perception Test (HPT), and a Hazard Change Detection Task (HCDT). Method Community dwelling drivers (n = 297) aged 65–96 were assessed using a battery of measures of cognitive and visual function. Results Factor analysis of these predictor variables yielded factors including Executive/Speed, Vision (measured by visual acuity and contrast sensitivity), Spatial, Visual Closure, and Working Memory. Cognitive and Vision factors explained 83–95% of age-related variance in the Capacity to Drive Safely. Spatial and Working Memory were associated with UFOV, HPT and HCDT, Executive/Speed was associated with UFOV and HCDT and Vision was associated with HPT. Conclusion The Capacity to Drive Safely declines with chronological age, and this decline is associated with age-related declines in several higher order cognitive abilities involving manipulation and storage of visuospatial information under speeded conditions. There are also age-independent effects of cognitive function and vision that determine driving safety.

Clinical strategies for the alleviation of contractures from a predictive mathematical model of dermal repair

Hypertrophic scars arise when there is an overproduction of collagen during wound healing. These are often associated with poor regulation of the rate of programmed cell death(apoptosis) of the cells synthesizing the collagen or by an exuberant inflammatory response that prolongs collagen production and increases wound contraction. Severe contractures that occur, for example, after a deep burn can cause loss of function especially if the wound is over a joint such as the elbow or knee. Recently, we have developed a morphoelastic mathematical model for dermal repair that incorporates the chemical, cellular and mechanical aspects of dermal wound healing. Using this model, we examine pathological scarring in dermal repair by first assuming a smaller than usual apoptotic rate for myofibroblasts, and then considering a prolonged inflammatory response, in an attempt to determine a possible optimal intervention strategy to promote normal repair, or terminate the fibrotic scarring response. Our model predicts that in both cases it is best to apply the intervention strategy early in the wound healing response. Further, the earlier an intervention is made, the less aggressive the intervention required. Finally, if intervention is conducted at a late time during healing, a significant intervention is required; however, there is a threshold concentration of the drug or therapy applied, above which minimal further improvement to wound repair is obtained.

A multi-level model of leadership in complex project management

Management (or perceived mismanagement) of large-scale, complex projects poses special problems and often results in spectacular failures, cost overruns, time blowouts and stakeholder dissatisfaction. While traditional project management responds with increasingly administrative constraints, we argue that leaders of such projects also need to display adaptive and enabling behaviours to foster adaptive processes, such as opportunity recognition, which requires an interaction of cognitive and affective processes of individual, project, and team leader attributes and behaviours. At the core of this model we propose is an interaction of cognitive flexibility, affect and emotional intelligence. The result of this interaction is enhanced leader opportunity recognition that, in turn, facilitates multilevel outcomes.

Test of a model of the effects of parental illness on youth and family functioning

Objective: Parental illness (PI) may have adverse impacts on youth and family functioning. Research in this area has suffered from the absence of a guiding comprehensive framework. This study tested a conceptual model of the effects of PI on youth and family functioning derived from the Family Ecology Framework (FEF; Pedersen & Revenson, 2005). Method. A total of 85 parents with multiple sclerosis and 127 youth completed questionnaires at Time 1 and 12 months later at Time 2. Results. Structural equation modeling results supported the FEF with regards to physical-illness disability. Specifically, the proposed mediators (role redistribution, stress, and stigma) were implicated in the processes that link parental disability to several domains of youth adjustment. The results suggest that the effects of parental depression (PD) are not mediated through these processes; rather, PD directly affects family functioning, which in turn mediates the effects onto youth adjustment. Family functioning further mediated between PD and youth well-being and behavioral-social difficulties. Conclusions. Although results support the effects of parental-illness disability on youth and family functioning via the proposed mediational mechanisms, the additive effects of PD on youth physical and mental health occur through direct and indirect (via family functioning) pathways, respectively.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

Reducing aggression on our roads : testing a comprehensive model of aggressive driving

Background: Trauma resulting from traffic crashes poses a significant problem in highly motorised countries. Over a million people worldwide are killed annually and 50 million are critically injured as a result of traffic collisions. In Australia, road crashes cost an average of $17 billion annually in personal loss of income and quality of life, organisational losses in productivity and workplace quality, and health care costs. Driver aggression has been identified as a key factor contributing to crashes, and many motorists report experiencing mild forms of aggression (e.g., rude gestures, horn honking). However despite this concern, driver aggression has received relatively little attention in empirical research, and existing research has been hampered by a number of methodological and conceptual shortcomings. Specifically, there has been substantial disagreement regarding what constitutes aggressive driving and a failure to examine both the situational factors and the emotional and cognitive processes underlying driver aggression. To enhance current understanding of aggressive driving, a model of driver aggression that highlights the cognitive and emotional processes at play in aggressive driving incidents is proposed. Aims: The research aims to improve current understanding of the complex nature of driver aggression by testing and refining a model of aggressive driving that incorporates the person-related and situational factors and the cognitive and emotional appraisal processes fundamental to driver aggression. In doing so, the research will assist to provide a clear definition of what constitutes aggressive driving, assist to identify on-road incidents that trigger driver aggression, and identify the emotional and cognitive appraisal processes that underlie driver aggression. Methods: The research involves three studies. Firstly, to contextualise the model and explore the cognitive and emotional aspects of driver aggression, a diary-based study using self-reports of aggressive driving events will be conducted with a general population of drivers. This data will be supplemented by in-depth follow-up interviews with a sub-sample of participants. Secondly, to test generalisability of the model, a large sample of drivers will be asked to respond to video-based scenarios depicting driving contexts derived from incidents identified in Study 1 as inciting aggression. Finally, to further operationalise and test the model an advanced driving simulator will be used with sample of drivers. These drivers will be exposed to various driving scenarios that would be expected to trigger negative emotional responses. Results: Work on the project has commenced and progress on the first study will be reported.

The development of a multi-segment kinematic model of footwear

In gait analysis, both shoe mounted and skin mounted markers have been used to quantify the movement of the foot inside the shoe. However, these models have not been demonstrated as reliable or accurate in shod conditions. The purpose of this study was to develop an accurate and reliable marker set to describe foot-shoe complex kinematics during stance phase.