Testing a framework for the quality of process models: A case study

Process modeling can be regarded as the currently most popular form of conceptual modeling. Research evidence illustrates how process modeling is applied across the different information system life cycle phases for a range of different applications, such as configuration of Enterprise Systems, workflow management, or software development. However, a detailed discussion of critical factors of the quality of process models is still missing. This paper proposes a framework consisting of six quality factors, which is derived from a comprehensive literature review. It then presents in a case study, a utility provider, who had designed various business process models for the selection of an Enterprise System. The paper summarizes potential means of conducting a successful process modeling initiative and evaluates the described modeling approach within the Guidelines of Modeling (GoM) framework. An outlook shows the potential lessons learnt, and concludes with insights to the next phases of this study.

Promoting sustainable urban development in fast growing city-regions : practices from Kuala Lumpur and Hong Kong

The Asia‐Pacific region is characterised by rapid population growth and urbanisation. These trends often result in an increasing consumption of land, which in turn lead to spatially expansive and discontinuous urban development. As a consequence, local communities and the environment face strong pressures. Many cities in the region have developed policies to tackle the issue of rapid growth and its associated consequences, for example climate change. The broad aim of this paper is to identify the nature, trends and strategies of growth management in major Asia‐Pacific city‐regions, and their implications for natural resource management and infrastructure provision. More specifically, this research seeks to provide insights on sustainable urban development practice, particularly on the promotion of compact urbanisation within the Asia‐Pacific’s fastest growing regions. The methodology of the paper includes a detailed literature review and a comparative analysis of existing strategies and policies. The literature review focuses on the key concepts related to sustainable urban growth management. It also includes existing applications of urban growth management approaches and planning information system in managing growth. Following the literature review, the paper undertakes a comparative analysis of the strategies of major Asia‐Pacific city‐regions of Kuala Lumpur and Hong Kong in terms of their approaches to sustainable urban development. The findings of the paper provide a clear understanding of the necessity of sustainable urban development practices. It contributes to the development of a substantial base for further research. Ultimately, this research aims to shed light on sustainable urban development by providing insights on the management of growth, natural resources and urban infrastructures.

Web-based public participatory GIS

Decision support systems (DSS) have evolved rapidly during the last decade from stand alone or limited networked solutions to online participatory solutions. One of the major enablers of this change is the fastest growing areas of geographical information system (GIS) technology development that relates to the use of the Internet as a means to access, display, and analyze geospatial data remotely. World-wide many federal, state, and particularly local governments are designing to facilitate data sharing using interactive Internet map servers. This new generation DSS or planning support systems (PSS), interactive Internet map server, is the solution for delivering dynamic maps and GIS data and services via the world-wide Web, and providing public participatory GIS (PPGIS) opportunities to a wider community (Carver, 2001; Jankowski & Nyerges, 2001). It provides a highly scalable framework for GIS Web publishing, Web-based public participatory GIS (WPPGIS), which meets the needs of corporate intranets and demands of worldwide Internet access (Craig, 2002). The establishment of WPPGIS provides spatial data access through a support centre or a GIS portal to facilitate efficient access to and sharing of related geospatial data (Yigitcanlar, Baum, & Stimson, 2003). As more and more public and private entities adopt WPPGIS technology, the importance and complexity of facilitating geospatial data sharing is growing rapidly (Carver, 2003). Therefore, this article focuses on the online public participation dimension of the GIS technology. The article provides an overview of recent literature on GIS and WPPGIS, and includes a discussion on the potential use of these technologies in providing a democratic platform for the public in decision-making.

FM as a Business Enabler

As a functioning performing arts centre, commercial enterprise, tourist attraction and major national asset, Sydney Opera House must continue to demonstrate the optimal use and effectiveness of its facilities management (FM) to provide value for its stakeholders. To better achieve this, the Cooperative Research Centre for Construction Innovation focussed on the following three themes for investigation in the FM Exemplar Project — Sydney Opera House: digital modelling — developing a building information model capable of integrating information from disparate software systems and hard copy, and combining this with a spatial 3D computeraided design (CAD)/geographic information system (GIS) platform. This model offers a visual representation of the building and its component elements in 3D, and provides comprehensive information on each element. The model can work collaboratively through an open data exchange standard (common to all compliant software) in order to mine the data required to further FM objectives (such as maintenance) more efficiently and effectively. services procurement — developing a multi-criteria performance-based procurement framework aligned with organisational objectives for FM service delivery performance benchmarking — developing an FM benchmarking framework that enables facilities/ organisations to develop key performance indicators (KPIs) to identify better practice and improvement strategies. These three research stream outcomes were then aligned within the broader context of Sydney Opera House’s Total Asset Management (TAM) Plan and Strategic Asset Maintenance (SAM) Plan in arriving at a business framework aligned with, and in support of, organisational objectives. The Sydney Opera House is managed by the Sydney Opera House Trust on behalf of the Government of the State of New South Wales. Within the framework of the TAM Plan prepared in accordance with NSW Treasury Guidelines, the assimilation of these three themes provides an integrated FM solution capable of supporting Sydney Opera House’s business objectives and functional requirements. FM as a business enabler showcases innovative methods in improving FM performance, a better alignment of service and performance objectives and provides a better-practice model to support the business enterprise.

Fatal motorcycle crashes in north Queensland : characteristics and potential interventions

Aims: The Rural and Remote Road Safety Study (RRRSS) addresses a recognised need for greater research on road trauma in rural and remote Australia, the costs of which are disproportionately high compared with urban areas. The 5-year multi-phase study with whole-of-government support concluded in June 2008. Drawing on RRRSS data, we analysed fatal motorcycle crashes which occurred over 39 months to provide a description of crash characteristics, contributing factors and people involved. The descriptive analysis and discussion may inform development of tailored motorcycle safety interventions. Methods: RRRSS criteria sought vehicle crashes resulting in death or hospitalisation for 24 hours minimum of at least 1 person aged 16 years or over, in the study area defined roughly as the Queensland area north from Bowen in the east and Boulia in the west (excluding Townsville and Cairns urban areas). Fatal motorcycle crashes were selected from the RRRSS dataset. Analysis considered medical data covering injury types and severity, evidence of alcohol, drugs and prior medical conditions, as well as crash descriptions supplied by police to Queensland Transport on contributing circumstances, vehicle types, environmental conditions and people involved. Crash data were plotted in a geographic information system (MapInfo) for spatial analysis. Results: There were 23 deaths from 22 motorcycle crashes on public roads meeting RRRSS criteria. Of these, half were single vehicle crashes and half involved 2 or more vehicles. In contrast to general patterns for driver/rider age distribution in crashes, riders below 25 years of age were represented proportionally within the population. Riders in their thirties comprised 41% of fatalities, with a further 36% accounted for by riders in their fifties. 18 crashes occurred in the Far North Statistical Division (SD), with 2 crashes in both the Northern and North West SDs. Behavioural factors comprised the vast majority of contributing circumstances cited by police, with adverse environmental conditions noted in only 4 cases. Conclusions: Fatal motorcycle crashes were more likely to involve another vehicle and less likely to involve a young rider than non-fatal crashes recorded by the RRRSS. Rider behaviour contributed to the majority of crashes and should be a major focus of research, education and policy development, while other road users’ behaviour and awareness also remains important. With 68% of crashes occurring on major and secondary roads within a 130km radius of Cairns, efforts should focus on this geographic area.

Growing demand for emergency health services in Queensland, Australia

Introduction: The demand for emergency health services (EHS), both in the prehospital (ambulance) and hospital (emergency departments) settings, is growing rapidly in Australia. Broader health system changes have reduced available health infrastructure, particularly hospital beds, resulting in reduced access to and congestion of the EHS as demonstrated by longer waiting times and ambulance “ramping”. Ambulance ramping occurring when patients have a prolonged wait on the emergency vehicle due to the unavailability of hospital beds. This presentation will outline the trends in EHS demand in Queensland compared with the rest of Australia and factors that appear to be contributing to the growth in demand. Methods: Secondary analysis was conducted using data from publicly available sources. Data from the Queensland Ambulance Service and Queensland Health Emergency Department Information System (EDIS) also were analyzed. Results: The demand for ambulance services and emergency departments has been increasing at 8% and 4% per year over the last decade, respectively; while accessible hospital beds have reduced by almost 10% contributing to the emergency department congestion and possibly contributing to the prehospital demand. While the increase in the proportion of the elderly population seems to explain a great deal of the demand for EHS, other factors also influence this growth including patient characteristics, institutional and societal factors, economic, EHS arrangements, and clinical factors. Conclusions: Overcrowding of facilities that provide EHS are causing considerable community concern. This overcrowding is caused by the growing demand and reduced access. The causes of this growing demand are complex, and require further detailed analysis in order to quantify and qualify these causes in order to provide a resilient foundation of evidence for future policy direction.

Maintaining centralised application systems : a cross-country, cross-sector, cross-platform comparison

Past studies of software maintenance issues have largely concentrated on the average North American firm. While they have made a substantial contribution to good information system management practice, it is believed that further segmentation of sample data and cross-country comparisons will help to identify patterns of behaviour more akin to many less average organizations in North America and elsewhere. This paper compares the Singapore maintenance scene with the reported North American experience. Comparisons are also made between: Government organizations, Singapore corporations and multinational corporations (MNCs); mainframe and minicomputer installations; and fourth-generation language (4GL) and non-4GL computer installations. Study findings, while in many cases were similar to earlier US studies, do show the importance of Singapore's young application portfolio, the widespread usage of 4GLs and the severe maintenance personnel problems.

Incorporating interdependence in risk likelihood analysis to enhance diagnostics in condition monitoring

This research is aimed at addressing problems in the field of asset management relating to risk analysis and decision making based on data from a Supervisory Control and Data Acquisition (SCADA) system. It is apparent that determining risk likelihood in risk analysis is difficult, especially when historical information is unreliable. This relates to a problem in SCADA data analysis because of nested data. A further problem is in providing beneficial information from a SCADA system to a managerial level information system (e.g. Enterprise Resource Planning/ERP). A Hierarchical Model is developed to address the problems. The model is composed of three different Analyses: Hierarchical Analysis, Failure Mode and Effect Analysis, and Interdependence Analysis. The significant contributions from the model include: (a) a new risk analysis model, namely an Interdependence Risk Analysis Model which does not rely on the existence of historical information because it utilises Interdependence Relationships to determine the risk likelihood, (b) improvement of the SCADA data analysis problem by addressing the nested data problem through the Hierarchical Analysis, and (c) presentation of a framework to provide beneficial information from SCADA systems to ERP systems. The case study of a Water Treatment Plant is utilised for model validation.

Preliminary spatiotemporal analysis of the association between socio-environmental factors and suicide

Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.

Bustracker : digitally augmented public transportation

Public transportation is an environment with great potential for applying location-based services through mobile devices. The BusTracker study is looking at how real-time passenger information systems can provide a core platform to improve commuters’ experiences. These systems rely on mobile computing and GPS technology to provide accurate information on transport vehicle locations. BusTracker builds on this mobile computing platform and geospatial information. The pilot study is running on the open source BugLabs computing platform, using a GPS module for accurate location information.

Extending the IS-Impact Model into the higher education sector

The study addresses known limitations of what may be the most important dependent variable in Information Systems (IS) research; IS-Success or IS-Impact. The study is expected to force a deeper understanding of the broad notions of IS success and impact. The aims of the research are to: (1) enhance the robustness and minimize limitations of the IS-Impact model, and (2) introduce and operationalise a more rigorously validated IS Impact measurement model to Universities, as a reliable model for evaluating different Administrative Systems. In extending and further generalizing the IS-Impact model, the study will address contemporary validation issues.

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.

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.

Developing a model of technology appropriation: A Marxian perspective

This paper explores the philosophical origins of appropriation of Information Systems (IS) using Marxian and other socio-cultural theory. It provides an in-depth examination of appropriation and its application in extant IS theory. We develop a three-tier model using Marx’s foundational concepts and from this generate four propositions that we test in an empirical example of IS in anesthesia. Using Marxian theory, this paper seeks common ground among existing theories of technology appropriation in IS research. This work contributes to IS research by (1) opening philosophical discussions on appropriation and the human ↔ technology nexus, (2) drawing on these varying perspectives to propose a general conceptualization of technology appropriation and (3) providing a starting point towards a general causal model of technology appropriation.

Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush-tailed rock-wallaby petrogale penicillata

Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.