Decision support system architecture for consultant selection

Decision Support System (DSS) has played a significant role in construction project management. This has been proven that a lot of DSS systems have been implemented throughout the whole construction project life cycle. However, most research only concentrated in model development and left few fundamental aspects in Information System development. As a result, the output of researches are complicated to be adopted by lay person particularly those whom come from a non-technical background. Hence, a DSS should hide the abstraction and complexity of DSS models by providing a more useful system which incorporated user oriented system. To demonstrate a desirable architecture of DSS particularly in public sector planning, we aim to propose a generic DSS framework for consultant selection. It will focus on the engagement of engineering consultant for irrigation and drainage infrastructure. The DSS framework comprise from operational decision to strategic decision level. The expected result of the research will provide a robust framework of DSS for consultant selection. In addition, the paper also discussed other issues that related to the existing DSS framework by integrating enabling technologies from computing. This paper is based on the preliminary case study conducted via literature review and archival documents at Department of Irrigation and Drainage (DID) Malaysia. The paper will directly affect to the enhancement of consultant pre-qualification assessment and selection tools. By the introduction of DSS in this area, the selection process will be more efficient in time, intuitively aided qualitative judgment, and transparent decision through aggregation of decision among stakeholders.

Key organizational elements for effective information and knowledge management

Effective information and knowledge management (IKM) is critical to corporate success; yet, its actual establishment and management is not yet fully understood. We identify ten organizational elements that need to be addressed to ensure the effective implementation and maintenance of information and knowledge management within organizations. We define these elements and provide key characterizations. We then discuss a case study that describes the implementation of an information system (designed to support IKM) in a medical supplies organization. We apply the framework of organizational elements in our analysis to uncover the enablers and barriers in this systems implementation project. Our analysis suggests that taking the ten organizational elements into consideration when implementing information systems will assist practitioners in managing information and knowledge processes more effectively and efficiently. We discuss implications for future research.

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.

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.

On the usage of labels and icons in business process modeling

The value of business process models is dependent not only on the choice of graphical elements in the model, but also on their annotation with additional textual and graphical information. This research discusses the use of text and icons for labeling the graphical constructs in a process model. We use two established verb classification schemes to examine the choice of activity labels in process modeling practice. Based on our findings, we synthesize a set of twenty-five activity label categories. We propose a systematic approach for graphically representing these label categories through the use of graphical icons, such that the resulting process models are easier and more readily understandable by end users. Our findings contribute to an ongoing stream of research investigating the practice of process modeling and thereby contribute to the body of knowledge about conceptual modeling quality overall.

An epidemic of pain in an Australian radiology practice

This paper presents findings from a study of an organisationally mandated assimilation process of an enterprise-wide information system in a radiology practice in Australia. A number of interviews with radiologists, radiographers and administrative staff are used to explore the impact of institutional structures on the assimilation process. The case study develops an argument that culture within and outside the Australian Radiology Practice (ARP), social structures within the ARP and organisational-level management mandates have impacted on the assimilation process. The study develops a theoretical framework that integrates elements of social actor theory (Lamb & Kling, 2003) to provide a more fine-grained analysis concentrating on the relationship among the radiology practitioners, the technology (an enterprise-wide Health Information System) and a larger social milieu surrounding its use. This study offers several theoretical and practical implications for technology assimilation in the health and radiology industry regarding the important roles social interactions, individual self-perceptions, organisational mandates and policies can play in assimilating new ICTs.

Facilitating unlearning during implementation of new technology

Purpose – One of the critical issues for change management, particularly in relation to the implementation of new technologies, is the existence of prior knowledge and established mental models which may hinder change efforts. Understanding unlearning and how it might assist during organizational change is a way to address this resistance. The purpose of this paper is to present research designed to identify specific factors that facilitate unlearning. Design/methodology/approach – Drawing together issues identified as potential influencers of unlearning, a survey questionnaire was developed and administered in an Australian corporation undergoing large-scale change due to the implementation of an enterprise information system. The results were analyzed to identify specific factors that impact on unlearning. Findings – Findings from this paper identify factors that hinder or help the unlearning process during times of change including understanding the need for change, the level of organizational support and training, assessment of the change, positive experience and informal support, the organization's history of change, individual's prior outlooks, and individuals' feelings and expectations. Research limitations/implications – The use of only one organization does not allow for comparisons between organizations of different sizes, cultures or industries and therefore extension of this research is recommended. Practical implications – For practitioners, this paper provides specific elements at both the level of individuals and the organization that need to be considered for optimal unlearning during times of change. Originality/value – Previous literature on unlearning has been predominantly conceptual and theoretical. These empirical findings serve to further an earlier model based on qualitative research into potential influencers of unlearning.

Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.

Knowledge-based approach for planning healthy cities : the case of Logan-Beaudesert, Australia

Introduction - The planning for healthy cities faces significant challenges due to lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges for planning healthy cities have been magnified by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and knowledge-based decisions. Some studies have suggested that the use of a ‘knowledge-based’ approach to planning will enhance the accuracy and quality decision-making by improving the availability of data and information for health service planners and may also lead to increased collaboration between stakeholders and the community. A knowledge-based or evidence-based approach to decision-making can provide an ‘out-of-the-box’ thinking through the use of technology during decision-making processes. Minimal research has been conducted in this area to date, especially in terms of evaluating the impact of adopting knowledge-based approach on stakeholders, policy-makers and decision-makers within health planning initiatives. Purpose – The purpose of the paper is to present an integrated method that has been developed to facilitate a knowledge-based decision-making process to assist health planning Methodology – Specifically, the paper describes the participatory process that has been adopted to develop an online Geographic Information System (GIS)-based Decision Support System (DSS) for health planners. Value – Conceptually, it is an application of Healthy Cities and Knowledge Cities approaches which are linked together. Specifically, it is a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This setting-based initiative is named as the Logan-Beaudesert Health Coalition (LBHC). Practical implications - The paper outlines the application of a knowledge-based approach to the development of a healthy city. Also, it focuses on the need for widespread use of this approach as a tool for enhancing community-based health coalition decision making processes.

An evaluation of IS-impact utility and intuitiveness

This study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable et al, 2006). IS-Impact is defined as "a measure at a point in time, of the stream of net benefits from the IS [Information System], to date and anticipated, as perceived by all key-user-groups" (Gable Sedera and Chan, 2008). Track efforts have yielded the bicameral IS-Impact measurement model; the "impact" half includes Organizational-Impact and Individual-Impact dimensions; the "quality" half includes System-Quality and Information-Quality dimensions. The IS-Impact model, by design, is intended to be robust, simple and generalisable, to yield results that are comparable across time, stakeholders, different systems and system contexts. The model and measurement approach employs perceptual measures and an instrument that is relevant to key stakeholder groups, thereby enabling the combination or comparison of stakeholder perspectives. Such a validated and widely accepted IS-Impact measurement model has both academic and practical value. It facilitates systematic operationalisation of a main dependent variable in research (IS-Impact), which can also serve as an important independent variable. For IS management practice it provides a means to benchmark and track the performance of information systems in use. From examination of the literature, the study proposes that IS-Impact is an Analytic Theory. Gregor (2006) defines Analytic Theory simply as theory that ‘says what is’, base theory that is foundational to all other types of theory. The overarching research question thus is "Does IS-Impact positively manifest the attributes of Analytic Theory?" In order to address this question, we must first answer the question "What are the attributes of Analytic Theory?" The study identifies the main attributes of analytic theory as: (1) Completeness, (2) Mutual Exclusivity, (3) Parsimony, (4) Appropriate Hierarchy, (5) Utility, and (6) Intuitiveness. The value of empirical research in Information Systems is often assessed along the two main dimensions - rigor and relevance. Those Analytic Theory attributes associated with the ‘rigor’ of the IS-Impact model; namely, completeness, mutual exclusivity, parsimony and appropriate hierarchy, have been addressed in prior research (e.g. Gable et al, 2008). Though common tests of rigor are widely accepted and relatively uniformly applied (particularly in relation to positivist, quantitative research), attention to relevance has seldom been given the same systematic attention. This study assumes a mainly practice perspective, and emphasises the methodical evaluation of the Analytic Theory ‘relevance’ attributes represented by the Utility and Intuitiveness of the IS-Impact model. Thus, related research questions are: "Is the IS-Impact model intuitive to practitioners?" and "Is the IS-Impact model useful to practitioners?" March and Smith (1995), identify four outputs of Design Science: constructs, models, methods and instantiations (Design Science research may involve one or more of these). IS-Impact can be viewed as a design science model, composed of Design Science constructs (the four IS-Impact dimensions and the two model halves), and instantiations in the form of management information (IS-Impact data organised and presented for management decision making). In addition to methodically evaluating the Utility and Intuitiveness of the IS-Impact model and its constituent constructs, the study aims to also evaluate the derived management information. Thus, further research questions are: "Is the IS-Impact derived management information intuitive to practitioners?" and "Is the IS-Impact derived management information useful to practitioners? The study employs a longitudinal design entailing three surveys over 4 years (the 1st involving secondary data) of the Oracle-Financials application at QUT, interspersed with focus groups involving senior financial managers. The study too entails a survey of Financials at four other Australian Universities. The three focus groups respectively emphasise: (1) the IS-Impact model, (2) the 2nd survey at QUT (descriptive), and (3) comparison across surveys within QUT, and between QUT and the group of Universities. Aligned with the track goal of producing IS-Impact scores that are highly comparable, the study also addresses the more specific utility-related questions, "Is IS-Impact derived management information a useful comparator across time?" and "Is IS-Impact derived management information a useful comparator across universities?" The main contribution of the study is evidence of the utility and intuitiveness of IS-Impact to practice, thereby further substantiating the practical value of the IS-Impact approach; and also thereby motivating continuing and further research on the validity of IS-Impact, and research employing the ISImpact constructs in descriptive, predictive and explanatory studies. The study also has value methodologically as an example of relatively rigorous attention to relevance. A further key contribution is the clarification and instantiation of the full set of analytic theory attributes.

Spatial distribution of suicide in Queensland, Australia

Background: There has been a lack of investigation into the spatial distribution and clustering of suicide in Australia, where the population density is lower than many countries and varies dramatically among urban, rural and remote areas. This study aims to examine the spatial distribution of suicide at a Local Governmental Area (LGA) level and identify the LGAs with a high relative risk of suicide in Queensland, Australia, using geographical information system (GIS) techniques.---------- Methods: Data on suicide and demographic variables in each LGA between 1999 and 2003 were acquired from the Australian Bureau of Statistics. An age standardised mortality (ASM) rate for suicide was calculated at the LGA level. GIS techniques were used to examine the geographical difference of suicide across different areas.---------- Results: Far north and north-eastern Queensland (i.e., Cook and Mornington Shires) had the highest suicide incidence in both genders, while the south-western areas (i.e., Barcoo and Bauhinia Shires) had the lowest incidence in both genders. In different age groups (≤24 years, 25 to 44 years, 45 to 64 years, and ≥65 years), ASM rates of suicide varied with gender at the LGA level. Mornington and six other LGAs with low socioeconomic status in the upper Southeast had significant spatial clusters of high suicide risk.---------- Conclusions: There was a notable difference in ASM rates of suicide at the LGA level in Queensland. Some LGAs had significant spatial clusters of high suicide risk. The determinants of the geographical difference of suicide should be addressed in future research.

Planning online : a community-based interactive decision-making model

The first use of computing technologies and the development of land use models in order to support decision-making processes in urban planning date back to as early as mid 20th century. The main thrust of computing applications in urban planning is their contribution to sound decision-making and planning practices. During the last couple of decades many new computing tools and technologies, including geospatial technologies, are designed to enhance planners' capability in dealing with complex urban environments and planning for prosperous and healthy communities. This chapter, therefore, examines the role of information technologies, particularly internet-based geographic information systems, as decision support systems to aid public participatory planning. The chapter discusses challenges and opportunities for the use of internet-based mapping application and tools in collaborative decision-making, and introduces a prototype internet-based geographic information system that is developed to integrate public-oriented interactive decision mechanisms into urban planning practice. This system, referred as the 'Community-based Internet GIS' model, incorporates advanced information technologies, distance learning, sustainable urban development principles and community involvement techniques in decision-making processes, and piloted in Shibuya, Tokyo, Japan.

The effects of content presentation format and user characteristics on novice developers’ understanding of process models

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them being used for information systems development. In this paper, we examine two factors that we predict will influence the understanding of a business process that novice developers obtain from a corresponding process model: the content presentation form chosen to articulate the business domain, and the user characteristics of the novice developers working with the model. Our experimental study provides evidence that novice developers obtain similar levels of understanding when confronted with an unfamiliar or a familiar process model. However, previous modeling experience, the use of English as a second language, and previous work experience in BPM are important influencing factors of model understanding. Our findings suggest that education and research in process modeling should increase the focus on human factors and how they relate to content and content presentation formats for different modeling tasks. We discuss implications for practice and research.

Measuring the performance of Customs Information Systems (CIS) in Malaysia

In the scope of this study, ‘performance measurement’ includes the collection and presentation of relevant information that reflects progress in achieving organisational strategic aims and meeting the needs of stakeholders such as merchants, importers, exporters and other clients. Evidence shows that utilising information technology (IT) in customs matters supports import and export practices and ensures that supply chain management flows seamlessly. This paper briefly reviews some practical techniques for measuring performance. Its aim is to recommend a model for measuring the performance of information systems (IS): in this case, the Customs Information System (CIS) used by the Royal Malaysian Customs Department (RMCD).The study evaluates the effectiveness of CIS implementation measures in Malaysia from an IT perspective. A model based on IS theories will be used to assess the impact of CIS. The findings of this study recommend measures for evaluating the performance of CIS and its organisational impacts in Malaysia. It is also hoped that the results of the study will assist other Customs administrations evaluate the performance of their information systems.

Measuring the impact of information systems in Malaysia

Information Systems researchers have employed a diversity of sometimes inconsistent measures of IS success, seldom explicating the rationale, thereby complicating the choice for future researchers. In response to these and other issues, Gable, Sedera and Chan introduced the IS-Impact measurement model. This model represents “the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. Although the IS-Impact model was rigorously validated in previous research, there is a need to further generalise and validate it in different context. This paper reported the findings of the IS-Impact model revalidation study at four state governments in Malaysia with 232 users of a financial system that is currently being used at eleven state governments in Malaysia. Data was analysed following the guidelines for formative measurement validation using SmartPLS. Based on the PLS results, data supported the IS-Impact dimensions and measures thus confirming the validity of the IS-Impact model in Malaysia. This indicates that the IS-Impact model is robust and can be used across different context.