Networks in the shadow of markets and hierarchies : calling the shots in the visual effects industry

The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.

Mining trading partners’ preferences for efficient multi-issue bargaining in E‑business

Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e‑marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e‑marketplaces.

Merging business process models

This paper addresses the following problem: given two or more business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from an arbitrary collection of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back from which original model(s) does a given element in the merged model come from. The algorithm has been prototyped and tested against process models taken from several application domains.

The Alcohol Helplessness Scale and its prediction of depression among problem drinkers

Event-specific scales commonly have greater power than generalized scales in prediction of specific disorders and in testing mediator models for predicting such disorders. Therefore, in a preliminary study, a 6-item Alcohol Helplessness Scale was constructed and found to be reliable for a sample of 98 problem drinkers. Hierarchical multiple regression and its derivative path analysis were used to test whether helplessness and self-efficacy moderate or mediate the link between alcohol dependence and depression, A test of a moderation model was not supported, whereas a test of a mediation model was supported. Helplessness and self-efficacy both significantly and independently mediated between alcohol dependence and depression. Nevertheless, a significant direct effect of alcohol dependence on depression also remained.

Temperature enhanced effects of ozone on cardiovascular mortality in 95 large US communities, 1987-2000 - assessment using the NMMAPS data

A few studies examined interactive effects between air pollution and temperature on health outcomes. This study is to examine if temperature modified effects of ozone and cardiovascular mortality in 95 large US cities. A nonparametric and a parametric regression models were separately used to explore interactive effects of temperature and ozone on cardiovascular mortality during May and October, 1987-2000. A Bayesian meta-analysis was used to pool estimates. Both models illustrate that temperature enhanced the ozone effects on mortality in the northern region, but obviously in the southern region. A 10-ppb increment in ozone was associated with 0.41 % (95% posterior interval (PI): -0.19 %, 0.93 %), 0.27 % (95% PI: -0.44 %, 0.87 %) and 1.68 % (95% PI: 0.07 %, 3.26 %) increases in daily cardiovascular mortality corresponding to low, moderate and high levels of temperature, respectively. We concluded that temperature modified effects of ozone, particularly in the northern region.

Effective employment-based training models for childcare workers

Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (eg. Technical and Further Education) or university. Effective models of employment-based training are critical to provide training to highly competent workers. This paper presents findings from a study that examined current and emerging models of employment-based training in the childcare sector, particularly at the Diploma level. Semi-structured interviews were conducted with a sample of 16 participants who represented childcare directors, employers, and workers located in childcare services in urban, regional and remote locations in the State of Queensland. The study proposes a ‘best-fit’ employment-based training approach that is characterised by a compendium of five models instead of a ‘one size fits all’. Issues with successful implementation of the EBT models are also discussed

Mathematical models for describing the shape of the in vitro unstretched human crystalline lens

We developed orthogonal least-squares techniques for fitting crystalline lens shapes, and used the bootstrap method to determine uncertainties associated with the estimated vertex radii of curvature and asphericities of five different models. Three existing models were investigated including one that uses two separate conics for the anterior and posterior surfaces, and two whole lens models based on a modulated hyperbolic cosine function and on a generalized conic function. Two new models were proposed including one that uses two interdependent conics and a polynomial based whole lens model. The models were used to describe the in vitro shape for a data set of twenty human lenses with ages 7–82 years. The two-conic-surface model (7 mm zone diameter) and the interdependent surfaces model had significantly lower merit functions than the other three models for the data set, indicating that most likely they can describe human lens shape over a wide age range better than the other models (although with the two-conic-surfaces model being unable to describe the lens equatorial region). Considerable differences were found between some models regarding estimates of radii of curvature and surface asphericities. The hyperbolic cosine model and the new polynomial based whole lens model had the best precision in determining the radii of curvature and surface asphericities across the five considered models. Most models found significant increase in anterior, but not posterior, radius of curvature with age. Most models found a wide scatter of asphericities, but with the asphericities usually being positive and not significantly related to age. As the interdependent surfaces model had lower merit function than three whole lens models, there is further scope to develop an accurate model of the complete shape of human lenses of all ages. The results highlight the continued difficulty in selecting an appropriate model for the crystalline lens shape.

Models of supervision : from theory to practice

This chapter will address psychodynamic, cognitive-behavioural, and developmental models in supervision by initially considering the historical underpinnings of each and then examining in turn some of the key processes that are evident in the supervisory relationships. Case studies are included where appropriate to highlight the application of theory to practice and several processes are fully elaborated over all models to enable a contemporary view of style and substance in the supervision context.

The effect of language models on phonetic decoding for spoken term detection

Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task.

Assessing information systems success models : empirical comparison (Research in Progress)

Information System (IS) success may be the most arguable and important dependent variable in the IS field. The purpose of the present study is to address IS success by empirically assess and compare DeLone and McLean’s (1992) and Gable’s et al. (2008) models of IS success in Australian Universities context. The two models have some commonalities and several important distinctions. Both models integrate and interrelate multiple dimensions of IS success. Hence, it would be useful to compare the models to see which is superior; as it is not clear how IS researchers should respond to this controversy.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Elicitator : an expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

Simplified numerical models of LiteSteel Beam floor joists with Web openings for the prediction of section moment capacities

This paper is aimed at investigating the effect of web openings on the plastic bending behaviour and section moment capacity of a new cold-formed steel beam known as LiteSteel beam (LSB) using numerical modelling. Different LSB sections with varying circular hole diameter and spacing were considered. A simplified but appropriate numerical modelling technique was developed for the modelling of monosymmetric sections such as LSBs subject to bending, and was used to simulate a series of section moment capacity tests of LSB flexural members with web openings. The buckling and ultimate strength behaviour was investigated in detail and the modeling technique was further improved through a comparison of numerical and experimental results. This paper describes the simplified finite element modeling technique used in this study that includes all the significant behavioural effects affecting the plastic bending behaviour and section moment capacity of LSB sections with web holes. Numerical and test results and associated findings are also presented.

Socio-environmental factors and suicide in Queensland, Australia

Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.