Relevant bibliographies by topics / Decision support systems Australia

Academic literature on the topic 'Decision support systems Australia'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Decision support systems Australia.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Decision support systems Australia"

1

Buttery, Alan, and Rick Tamaschke. "Marketing Decision Support Systems and Australian Businesses: A Queensland Case Study and Implications Towards 2000." Journal of Management & Organization 3, no. 1 (January 1997): 51–58. http://dx.doi.org/10.1017/s183336720000599x.

Full text
Abstract:
AbstractLittle is known about the extent to which the Marketing Decision Support System (MDSS) technology is currently used in Australia, or about the scope for the technology in Australia towards the year 2000. This paper reports the results of recent survey research into MDSS in Queensland by industry sector (agriculture and mining, manufacturing, construction, and services). The results suggest that there is an urgent need to boost the pace of MDSS development in all industry sectors, and that this should be given a high priority in government policy initiatives to enhance Australia's competitive advantage. It is possible, otherwise, that the present gap in information usage between Australia and its competitors will widen, with consequent negative implications for the nation's current account deficit, foreign debt and unemployment.
APA, Harvard, Vancouver, ISO, and other styles
2

Buttery, Alan, and Rick Tamaschke. "Marketing Decision Support Systems and Australian Businesses: A Queensland Case Study and Implications Towards 2000." Journal of the Australian and New Zealand Academy of Management 3, no. 1 (January 1997): 51–58. http://dx.doi.org/10.5172/jmo.1997.3.1.51.

Full text
Abstract:
AbstractLittle is known about the extent to which the Marketing Decision Support System (MDSS) technology is currently used in Australia, or about the scope for the technology in Australia towards the year 2000. This paper reports the results of recent survey research into MDSS in Queensland by industry sector (agriculture and mining, manufacturing, construction, and services). The results suggest that there is an urgent need to boost the pace of MDSS development in all industry sectors, and that this should be given a high priority in government policy initiatives to enhance Australia's competitive advantage. It is possible, otherwise, that the present gap in information usage between Australia and its competitors will widen, with consequent negative implications for the nation's current account deficit, foreign debt and unemployment.
APA, Harvard, Vancouver, ISO, and other styles
3

Melbourne-Thomas, Jessica, Andrew J. Constable, Elizabeth A. Fulton, Stuart P. Corney, Rowan Trebilco, Alistair J. Hobday, Julia L. Blanchard, et al. "Integrated modelling to support decision-making for marine social–ecological systems in Australia." ICES Journal of Marine Science 74, no. 9 (May 26, 2017): 2298–308. http://dx.doi.org/10.1093/icesjms/fsx078.

Full text
Abstract:
Abstract Policy- and decision-makers require assessments of status and trends for marine species, habitats, and ecosystems to understand if human activities in the marine environment are sustainable, particularly in the face of global change. Central to many assessments are statistical and dynamical models of populations, communities, ecosystems, and their socioeconomic systems and management frameworks. The establishment of a national system that could facilitate the development of such model-based assessments has been identified as a priority for addressing management challenges for Australia’s marine environment. Given that most assessments require cross-scale information, individual models cannot capture all of the spatial, temporal, biological, and socioeconomic scales that are typically needed. Coupling or integrating models across scales and domains can expand the scope for developing comprehensive and internally consistent, system-level assessments, including higher-level feedbacks in social–ecological systems. In this article, we summarize: (i) integrated modelling for marine systems currently being undertaken in Australia, (ii) methods used for integration and comparison of models, and (iii) improvements to facilitate further integration, particularly with respect to standards and specifications. We consider future needs for integrated modelling of marine social–ecological systems in Australia and provide a set of recommendations for priority focus areas in the development of a national approach to integrated modelling. These recommendations draw on—and have broader relevance for—international efforts around integrated modelling to inform decision-making for marine systems.
APA, Harvard, Vancouver, ISO, and other styles
4

Bellamy, JA, D. Lowes, AJ Ash, JG Mcivor, and ND Macleod. "A Decision Support Approach to Sustainable Grazing Management for Spatially Heterogeneous Rangeland Paddocks." Rangeland Journal 18, no. 2 (1996): 370. http://dx.doi.org/10.1071/rj9960370.

Full text
Abstract:
Public concern for the way land resources are used has led to the introduction of legislation in several Australian States requiring the demonstration of sustainable use of the pastoral resource. However, no practical system of appraisal of sustainability in grazing management systems exists. The common situation facing decision-makers at policy and enterprise levels is one of inadequate, unobtainable or inappropriate data, or systematic indeterminacy. This necessitates erring on the side of caution, through an adaptive integrated approach to decision-making. Such an approach requires: (i) an understanding of the key processes that govern the interactions between livestock, plants, and heterogeneous landscape systems; (ii) the identification of indicators of potential problems in these systems at spatial and temporal scales relevant to human use and management; and (iii) the availability of effective tools to evaluate management options in terms of their risks to the sustainability of the grazing land resource, and the profitability of production. This paper describes a decision support approach to improving our understanding of the complexities of grazing management systems. The paper first proposes an integrated framework for a decision support system (DSS) for evaluating the sustainability of grazing management in terms of the risk of changes to the vegetation and soil resource, and the profitability of production. It then examines an application of a DSS approach, called Landassess DSS, to the tropical woodlands in northern Australia, and discusses the broader implications for sustainable management of extensive native pasture livestock production systems.
APA, Harvard, Vancouver, ISO, and other styles
5

Mullan, Leanne, Karen Wynter, Andrea Driscoll, and Bodil Rasmussen. "Implementation strategies to overcome barriers to diabetes-related footcare delivery in primary care: a qualitative study." Australian Journal of Primary Health 27, no. 4 (2021): 328. http://dx.doi.org/10.1071/py20241.

Full text
Abstract:
The aim of this study is to identify, from the perspectives of key health policy decision-makers, strategies that address barriers to diabetes-related footcare delivery in primary care, and outline key elements required to support implementation into clinical practice. The study utilised a qualitative design with inductive analysis approach. Seven key health policy decisions-makers within Australia were interviewed. Practical strategies identified to support provision and delivery of foot care in primary care were: (a) building on current incentivisation structures through quality improvement projects; (b) enhancing education and community awareness; (c) greater utilisation and provision of resources and support systems; and (d) development of collaborative models of care and referral pathways. Key elements reported to support effective implementation of footcare strategies included developing and implementing strategies based on co-design, consultation, collaboration, consolidation and co-commissioning. To the authors’ knowledge, this is the first Australian study to obtain information from key health policy decision-makers, identifying strategies to support footcare delivery in primary care. Implementation of preventative diabetes-related footcare strategies into ‘routine’ primary care clinical practice requires multiparty co-design, consultation, consolidation, collaboration and co-commissioning. The basis of strategy development will influence implementation success and thus improve outcomes for people living with diabetes.
APA, Harvard, Vancouver, ISO, and other styles
6

Hochman, Z., H. van Rees, P. S. Carberry, J. R. Hunt, R. L. McCown, A. Gartmann, D. Holzworth, et al. "Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate." Crop and Pasture Science 60, no. 11 (2009): 1057. http://dx.doi.org/10.1071/cp09020.

Full text
Abstract:
In Australia, a land subject to high annual variation in grain yields, farmers find it challenging to adjust crop production inputs to yield prospects. Scientists have responded to this problem by developing Decision Support Systems, yet the scientists’ enthusiasm for developing these tools has not been reciprocated by farm managers or their advisers, who mostly continue to avoid their use. Preceding papers in this series described the FARMSCAPE intervention: a new paradigm for decision support that had significant effects on farmers and their advisers. These effects were achieved in large measure because of the intensive effort which scientists invested in engaging with their clients. However, such intensive effort is time consuming and economically unsustainable and there remained a need for a more cost-effective tool. In this paper, we report on the evolution, structure, and performance of Yield Prophet®: an internet service designed to move on from the FARMSCAPE model to a less intensive, yet high quality, service to reduce farmer uncertainty about yield prospects and the potential effects of alternative management practices on crop production and income. Compared with conventional Decision Support Systems, Yield Prophet offers flexibility in problem definition and allows farmers to more realistically specify the problems in their fields. Yield Prophet also uniquely provides a means for virtual monitoring of the progress of a crop throughout the season. This is particularly important for in-season decision support and for frequent reviewing, in real time, of the consequences of past decisions and past events on likely future outcomes. The Yield Prophet approach to decision support is consistent with two important, but often ignored, lessons from decision science: that managers make their decisions by satisficing rather than optimising and that managers’ fluid approach to decision making requires ongoing monitoring of the consequences of past decisions.
APA, Harvard, Vancouver, ISO, and other styles
7

Noble, James C., and Paul Walker. "Integrated shrub management in semi-arid woodlands of eastern Australia: A systems-based decision support model." Agricultural Systems 88, no. 2-3 (June 2006): 332–59. http://dx.doi.org/10.1016/j.agsy.2005.06.018.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Atkinson, Jo-An, Adam Skinner, Sue Hackney, Linda Mason, Mark Heffernan, Dianne Currier, Kylie King, and Jane Pirkis. "Systems modelling and simulation to inform strategic decision making for suicide prevention in rural New South Wales (Australia)." Australian & New Zealand Journal of Psychiatry 54, no. 9 (June 17, 2020): 892–901. http://dx.doi.org/10.1177/0004867420932639.

Full text
Abstract:
Background: The need to understand and respond to the unique characteristics and drivers of suicidal behaviour in rural areas has been enabled through the Australian Government’s 2015 mental health reforms facilitating a move to an evidence-based, regional approach to suicide prevention. However, a key challenge has been the complex decision-making environment and lack of appropriate tools to facilitate the use of evidence, data and expert knowledge in a way that can inform contextually appropriate strategies that will deliver the greatest impact. This paper reports the co-development of an advanced decision support tool that enables regional decision makers to explore the likely impacts of their decisions before implementing them in the real world. Methods: A system dynamics model for the rural and remote population catchment of Western New South Wales was developed. The model was based on defined pathways to mental health care and suicidal behaviour and reproduced historic trends in the incidence of attempted suicide (self-harm hospitalisations) and suicide deaths in the region. A series of intervention scenarios were investigated to forecast their impact on suicidal behaviour over a 10-year period. Results: Post-suicide attempt assertive aftercare was forecast to deliver the greatest impact, reducing the numbers of self-harm hospitalisations and suicide deaths by 5.65% (95% interval, 4.87−6.42%) and 5.45% (4.68−6.22%), respectively. Reductions were also projected for community support programs (self-harm hospitalisations: 2.83%, 95% interval 2.23−3.46%; suicide deaths: 4.38%, 95% interval 3.78−5.00%). Some scenarios produced unintuitive impacts or effect sizes that were significantly lower than what has been anticipated under the traditional evidence-based approach to suicide prevention and provide an opportunity for learning. Conclusion: Systems modelling and simulation offers significant potential for regional decision makers to better understand and respond to the unique characteristics and drivers of suicidal behaviour in their catchments and more effectively allocate limited health resources.
APA, Harvard, Vancouver, ISO, and other styles
9

Williams, Paul. "A regulation evaluation system: a decision support system for the Building Code of Australia." Construction Management and Economics 13, no. 3 (May 1995): 197–208. http://dx.doi.org/10.1080/01446199500000024.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Laka, Mah, Adriana Milazzo, and Tracy Merlin. "Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management." International Journal of Environmental Research and Public Health 18, no. 4 (February 16, 2021): 1901. http://dx.doi.org/10.3390/ijerph18041901.

Full text
Abstract:
The study evaluated individual and setting-specific factors that moderate clinicians’ perception regarding use of clinical decision support systems (CDSS) for antibiotic management. A cross-sectional online survey examined clinicians’ perceptions about CDSS implementation for antibiotic management in Australia. Multivariable logistic regression determined the association between drivers of CDSS adoption and different moderators. Clinical experience, CDSS use and care setting were important predictors of clinicians’ perception concerning CDSS adoption. Compared to nonusers, CDSS users were less likely to lack confidence in CDSS (OR = 0.63, 95%, CI = 0.32, 0.94) and consider it a threat to professional autonomy (OR = 0.47, 95%, CI = 0.08, 0.83). Conversely, there was higher likelihood in experienced clinicians (>20 years) to distrust CDSS (OR = 1.58, 95%, CI = 1.08, 2.23) due to fear of comprising their clinical judgement (OR = 1.68, 95%, CI = 1.27, 2.85). In primary care, clinicians were more likely to perceive time constraints (OR = 1.96, 95%, CI = 1.04, 3.70) and patient preference (OR = 1.84, 95%, CI = 1.19, 2.78) as barriers to CDSS adoption for antibiotic prescribing. Our findings provide differentiated understanding of the CDSS implementation landscape by identifying different individual, organisational and system-level factors that influence system adoption. The individual and setting characteristics can help understand the variability in CDSS adoption for antibiotic management in different clinicians.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Decision support systems Australia"

1

Robinson, Jeffrey Brett, University of Western Sydney, of Science Technology and Environment College, and School of Environment and Agriculture. "Understanding and applying decision support systems in Australian farming systems research." THESIS_CSTE_EAG_Robinson_J.xml, 2005. http://handle.uws.edu.au:8081/1959.7/642.

Full text
Abstract:
Decision support systems (DSS) are usually based on computerised models of biophysical and economic systems. Despite early expectations that such models would inform and improve management, adoption rates have been low, and implementation of DSS is now “critical” The reasons for this are unclear and the aim of this study is to learn to better design, develop and apply DSS in farming systems research (FSR). Previous studies have explored the merits of quantitative tools including DSS, and suggested changes leading to greater impact. In Australia, the changes advocated have been: Simple, flexible, low cost economic tools: Emphasis on farmer learning through soft systems approaches: Understanding the socio-cultural contexts of using and developing DSS: Farmer and researcher co-learning from simulation modelling and Increasing user participation in DSS design and implementation. Twenty-four simple criteria were distilled from these studies, and their usefulness in guiding the development and application of DSS were assessed in six FSR case studies. The case studies were also used to better understand farmer learning through models of decision making and learning. To make DSS useful complements to farmers’ existing decision-making repertoires, they should be based on: (i) a decision-oriented development process, (ii) identifying a motivated and committed audience, (iii) a thorough understanding of the decision-makers context, (iv) using learning as the yardstick of success, and (v) understanding the contrasts, contradictions and conflicts between researcher and farmer decision cultures
Doctor of Philosophy (PhD)
APA, Harvard, Vancouver, ISO, and other styles
2

Barton, John Edward Built Environment Faculty of Built Environment UNSW. "A spatial decision support system for the management of public housing." Awarded by:University of New South Wales, 2007. http://handle.unsw.edu.au/1959.4/35209.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Purnomo, Deavi. "Developing collaborative planning support tools for optimised farming in Western Australia." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/2295.

Full text
Abstract:
Land-use (farm) planning is a highly complex and dynamic process. A land-use plan can be optimal at one point in time, but its currency can change quickly due to the dynamic nature of the variables driving the land-use decision-making process. These include external drivers such as weather and produce markets, that also interact with the biophysical interactions and management activities of crop production.The active environment of an annual farm planning process can be envisioned as being cone-like. At the beginning of the sowing year, the number of options open to the manager is huge, although uncertainty is high due to the inability to foresee future weather and market conditions. As the production year reveals itself, the uncertainties around weather and markets become more certain, as does the impact of weather and management activities on future production levels. This restricts the number of alternative management options available to the farm manager. Moreover, every decision made, such as crop type sown in a paddock, will constrains the range of management activities possible in that paddock for the rest of the growing season.This research has developed a prototype Land-use Decision Support System (LUDSS) to aid farm managers in their tactical farm management decision making. The prototype applies an innovative approach that mimics the way in which a farm manager and/or consultant would search for optimal solutions at a whole-farm level. This model captured the range of possible management activities available to the manager and the impact that both external (to the farm) and internal drivers have on crop production and the environment. It also captured the risk and uncertainty found in the decision space.The developed prototype is based on a Multiple Objective Decision-making (MODM) - á Posteriori approach incorporating an Exhaustive Search method. The objective set used for the model is: maximising profit and minimising environmental impact. Pareto optimisation theory was chosen as the method to select the optimal solution and a Monte Carlo simulator is integrated into the prototype to incorporate the dynamic nature of the farm decision making process. The prototype has a user-friendly front and back end to allow farmers to input data, drive the application and extract information easily.
APA, Harvard, Vancouver, ISO, and other styles
4

Mackrell, Dale Carolyn, and n/a. "Women as Farm Partners: Agricultural Decision Support Systems in the Australian Cotton Industry." Griffith University. Griffith Business School, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070305.131533.

Full text
Abstract:
Australian farmers are supplementing traditional practices with innovative strategies in an effort to survive recent economic, environmental, and social crises in the rural sector. These innovative strategies include moving towards a technology-based farm management style. A review of past literature determines that, despite a growing awareness of the usefulness of computers for farm management, there is concern over the limited demand for computer-based agricultural decision support systems (DSS). Recent literature indicates that women are the dominant users of computers on family farms yet are hesitant to use computers for decision support, and it is also unclear what decision-making roles women assume on family farms. While past research has investigated the roles of women in the Australian rural sector, there is a dearth of research into the interaction of women cotton growers with computers. Therefore, this dissertation is an ontological study and aims to contribute to scholarly knowledge in the research domain of Australian women cotton growers, agricultural DSS, and cotton farm management. This dissertation belongs in the Information Systems (IS) stream and describes an interpretive single case study which explores the lives of Australian women cotton growers on family farms and the association of an agricultural DSS with their farm management roles. Data collection was predominantly through semi-structured interviews with women cotton growers and cotton industry professionals such as DSS developers, rural extension officers, researchers and educators, rural experimental scientists, and agronomists and consultants, all of whom advise cotton growers. The study was informed by multiple sociological theories with opposing paradigmatic assumptions: Giddens' (1984) structuration theory as a metatheory to explore the recursiveness of farm life and technology usage; Rogers' (1995) diffusion of innovations theory with a functionalist approach to objectively examine the features of the software and user, as well as the processes of technology adoption; and Connell's (2002) theory of gender relations with its radical humanist perspective to subjectively investigate the relationships between farm partners through critical enquiry. The study was enriched further by drawing on other writings of these authors (Connell 1987; Giddens 2001; Rogers 2003) as well as complementary theories by authors (Orlikowski 1992; Orlikowski 2000; Trauth 2002; Vanclay & Lawrence 1995). These theories in combination have not been used before, which is a theoretical contribution of the study. The agricultural DSS for the study was CottonLOGIC, an advanced farm management tool to aid the management of cotton production. It was developed in the late 1990s by the CSIRO and the Australian Cotton Cooperative Research Centre (CRC), with support from the Cotton Research and Development Corporation (CRDC). CottonLOGIC is a software package of decision support and record-keeping modules to assist cotton growers and their advisors in the management of cotton pests, soil nutrition, and farm operations. It enables the recording and reporting of crop inputs and yields, insect populations (heliothis, tipworm, mirids and so on), weather data, and field operations such as fertiliser and pesticide applications, as well as the running of insect density prediction (heliothis and mites) and soil nutrition models. The study found that innovative practices and sustainable solutions are an imperative in cotton farm management for generating an improved triple bottom line of economic, environmental and social outcomes. CottonLOGIC is an industry benchmark for supporting these values through the incorporation of Best Management Practices (BMP) and Integrated Pest Management (IPM) principles, although there were indications that the software is in need of restructuring as could be expected of software over five years old. The evidence from the study was that women growers are participants in strategic farm decisions but less so in operational decisions, partly due to their lack of relevant agronomic knowledge. This hindered their use of CottonLOGIC, despite creative attempts to modify it. The study endorsed the existence of gender differences and inequalities in rural Australia. Nevertheless, the study also found that the women are valued for their roles as business partners in the multidisciplinary nature of farm management. All the same, there was evidence that greater collaboration and cooperation by farm partners and advisors would improve business outcomes. On the whole, however, women cotton growers are not passive agents but take responsibility for their own futures. In particular, DSS tools such as CottonLOGIC are instrumental in enabling women cotton growers to adapt to, challenge, and influence farm management practices in the family farm enterprise, just as CottonLOGIC is itself shaped and reshaped. Hence, a practical contribution of this study is to provide non-prescriptive guidelines for the improved adoption of agricultural DSS, particularly by rural women, as well as increasing awareness of the worth of their roles as family farm business partners.
APA, Harvard, Vancouver, ISO, and other styles
5

Gudes, Ori. "Developing a framework for planning healthy communities : the Logan Beaudesert health decision support system." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/50783/1/Ori_Gudes_Thesis.pdf.

Full text
Abstract:
In the last few decades, the focus on building healthy communities has grown significantly (Ashton, 2009). There is growing evidence that new approaches to planning are required to address the challenges faced by contemporary communities. These approaches need to be based on timely access to local information and collaborative planning processes (Murray, 2006; Scotch & Parmanto, 2006; Ashton, 2009; Kazda et al., 2009). However, there is little research to inform the methods that can support this type of responsive, local, collaborative and consultative health planning (Northridge et al., 2003). Some research justifies the use of decision support systems (DSS) as a tool to support planning for healthy communities. DSS have been found to increase collaboration between stakeholders and communities, improve the accuracy and quality of the decision-making process, and improve the availability of data and information for health decision-makers (Nobre et al., 1997; Cromley & McLafferty, 2002; Waring et al., 2005). Geographic information systems (GIS) have been suggested as an innovative method by which to implement DSS because they promote new ways of thinking about evidence and facilitate a broader understanding of communities. Furthermore, literature has indicated that online environments can have a positive impact on decision-making by enabling access to information by a broader audience (Kingston et al., 2001). However, only limited research has examined the implementation and impact of online DSS in the health planning field. Previous studies have emphasised the lack of effective information management systems and an absence of frameworks to guide the way in which information is used to promote informed decisions in health planning. It has become imperative to develop innovative approaches, frameworks and methods to support health planning. Thus, to address these identified gaps in the knowledge, this study aims to develop a conceptual planning framework for creating healthy communities and examine the impact of DSS in the Logan Beaudesert area. Specifically, the study aims to identify the key elements and domains of information that are needed to develop healthy communities, to develop a conceptual planning framework for creating healthy communities, to collaboratively develop and implement an online GIS-based Health DSS (i.e., HDSS), and to examine the impact of the HDSS on local decision-making processes. The study is based on a real-world case study of a community-based initiative that was established to improve public health outcomes and promote new ways of addressing chronic disease. The study involved the development of an online GIS-based health decision support system (HDSS), which was applied in the Logan Beaudesert region of Queensland, Australia. A planning framework was developed to account for the way in which information could be organised to contribute to a healthy community. The decision support system was developed within a unique settings-based initiative Logan Beaudesert Health Coalition (LBHC) designed to plan and improve the health capacity of Logan Beaudesert area in Queensland, Australia. This setting provided a suitable platform to apply a participatory research design to the development and implementation of the HDSS. Therefore, the HDSS was a pilot study examined the impact of this collaborative process, and the subsequent implementation of the HDSS on the way decision-making was perceived across the LBHC. As for the method, based on a systematic literature review, a comprehensive planning framework for creating healthy communities has been developed. This was followed by using a mixed method design, data were collected through both qualitative and quantitative methods. Specifically, data were collected by adopting a participatory action research (PAR) approach (i.e., PAR intervention) that informed the development and conceptualisation of the HDSS. A pre- and post-design was then used to determine the impact of the HDSS on decision-making. The findings of this study revealed a meaningful framework for organising information to guide planning for healthy communities. This conceptual framework provided a comprehensive system within which to organise existing data. The PAR process was useful in engaging stakeholders and decision-making in the development and implementation of the online GIS-based DSS. Through three PAR cycles, this study resulted in heightened awareness of online GIS-based DSS and openness to its implementation. It resulted in the development of a tailored system (i.e., HDSS) that addressed the local information and planning needs of the LBHC. In addition, the implementation of the DSS resulted in improved decision- making and greater satisfaction with decisions within the LBHC. For example, the study illustrated the culture in which decisions were made before and after the PAR intervention and what improvements have been observed after the application of the HDSS. In general, the findings indicated that decision-making processes are not merely informed (consequent of using the HDSS tool), but they also enhance the overall sense of ‗collaboration‘ in the health planning practice. For example, it was found that PAR intervention had a positive impact on the way decisions were made. The study revealed important features of the HDSS development and implementation process that will contribute to future research. Thus, the overall findings suggest that the HDSS is an effective tool, which would play an important role in the future for significantly improving the health planning practice.
APA, Harvard, Vancouver, ISO, and other styles
6

Mohammad, Alamgir Hossain. "Adoption, continued, and extended use of radio frequency identification (RFID) technology : Australian Livestock Industry." Thesis, Curtin University, 2012. http://hdl.handle.net/20.500.11937/1766.

Full text
Abstract:
In general, the adoption and diffusion of Information Systems (IS) in agriculture industry is a neglected issue in academia, let alone the livestock sector. In livestock industry, Radio Frequency Identification (RFID) technology is currently used in order to ensure meat safety. Generally, the livestock supply chain involves a large number of people and organisations/farms. To ensure a successful animal-tracing system, the examination of the adoption behaviour of those stakeholders is worthwhile. So far, no initiative has been made by the researchers to investigate the adoption process and relevant factors in a livestock setting. This research aims to close this research-gap. Furthermore, the ultimate success of an innovation is dependent not just on the adoption but on its continued and extended use. Scholars have been investigating on adoption and continuance behaviour of an innovation but not in an integrated fashion.This current research has studied both the adoption and continued and extended usage behaviour of Australian livestock industry regarding RFID technology in a single framework. Moreover, the extension decision of an innovation is a continuous and complex process. It is not easy for farms to identify a correct extension application from many possibilities. As has not been done yet a Decision Support System (DSS), which is based on Analytical Hierarchy Process (AHP), is developed in this research aiming to aid farms to choose the best extension-project.It is assumed that the adoption factors in a mandatory environment would be different than that of in a voluntary environment. In literature, it is very rare to find a comparative study of the adoption factors of a single innovation in both voluntary and mandatory environments. This research studied the both environments.This research adopted the ‘mixed method’ methodology. Face-to-face direct interview with semi-structured questionnaire has been used for the collection of qualitative data. Data obtained from the field study have been analysed using NVivo software package. On the other hand, Partial Least Square (PLS)-based Structural Equation Modelling (SEM) technique has been used for analysing the quantitative data obtained from a national survey on the variables identified earlier from the qualitative method.The findings of this research confirmed that environmental factors, organisational factors, and technological factors influence the adoption of RFID technology in livestock industry. The continued use and extended use of RFID systems are dependent on satisfaction obtained from using the current system. Moreover, confirmation bridges the adoption and continuance; this is the stage which influences the further-use of an innovation after being adopted.This current research has both theoretical and practical implications. Investigating the adoption factors along with continued and extended use factors in a single framework is a unique initiative by far in literature. This research strengthens the adoption-diffusion research of IS by getting insights from the livestock sector. Using the factors and variables, obtained from the research to develop a practical decision making process (i.e., the DSS) is innovative. As practical implications, governments and other organisations that have the power to make an industry to adopt an innovation should consider the findings of this study for efficient policy development and implementation. Similarly, the innovation-vendors/manufacturers may look at the derived factors for a successful acceptance of an innovation. Finally, the DSS does have the merit to be made more extensive and used at farm level in order to assist the farm decision-makers to choose their extension projects.
APA, Harvard, Vancouver, ISO, and other styles
7

Amein, Hussein Aly Abbass. "Computational intelligence techniques for decision making : with applications to the dairy industry." Thesis, Queensland University of Technology, 2000. https://eprints.qut.edu.au/36867/1/36867_Digitised%20Thesis.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Hodges, S. Lesley. "Electronic meeting systems – what they are and how they could benefit Australian government organisations." Thesis, Canberra, ACT : The Australian National University, 2011. http://hdl.handle.net/1885/7178.

Full text
Abstract:
Meetings are very important in any organisation and the Australian public service is no exception. Unfortunately, meetings are costly and time consuming, and often are ineffective and inefficient. Participants are regularly left with feelings of dissatisfaction after the meeting. Electronic meeting systems (EMS) were first developed in the United States in the 1980s to make meetings more effective and efficient. They are now more user-friendly, internet-connected and support multimedia. However, EMS have not been adopted to the extent that could be expected. This study draws from an extensive literature review supplemented by three case studies of Australian companies that provide EMS products and services (Global Learning Pty Ltd, Grouputer Pty Ltd and Zing Technologies Pty Ltd). The study provides answers to six questions: • What are electronic meeting systems (EMS)? • What is the evidence that using an EMS does improve meeting productivity (efficiency and effectiveness) and satisfaction? • Are there other benefits from using these systems? • How does the use of an EMS bring about these improvements in meetings and group collaboration? • What factors need to be managed in order for the organisation to obtain the most benefit from these systems? • Could EMS be used to improve meetings and business processes in Australian (including state/territory) government organisations? The study concluded that EMS could be used to great benefit to improve meetings and their outcomes for an enormous range of tasks that are carried out in all levels in the Australian public sector. EMS have successfully supported meeting sizes from two people to 700, and an even larger number of participants is possible.
APA, Harvard, Vancouver, ISO, and other styles
9

Alkarouri, Muhammad Abdulmuneim. "Distributed decision support systems." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555644.

Full text
Abstract:
Decision support systems are a class of computer based systems that assist in some or all levels of decision making within an organisation. Recently, the growth of data captured that is useful or even critical to the successful running or conclusion of projects in science and industry has been remarkable. Thus, the development of decision support systems that are scalable in terms of the size of data processed. the number of stakeholders, and their geographical span has become of the essence. This thesis identifies the issues in developing distributed decision support systems. Building on that. an architectural style for the development of scalable and extensible software systems is introduced. Subsequently, a framework for the design of distributed decision support systems is developed. This new architectural style is the Resource Oriented Services Architecture (ROSA). It builds on Representational State Transfer (REST), an architectural style that describes the venerable design of the world wide web. An architectural design based on REST revolves around resources, representations, and hyperlinks. \Vhat it lacks is a standardised way to represent computations as resources in a scalable and extensible manner. For systems that cannot be adequately described as a web of documents, this is a shortcoming. ROSA overcomes this by defining a means of representing executable resources in a manner that is consistent with the statelessness and cacheability constraints of REST. The resulting architecture enables the scalability of the system. Additionally, desirable features such as dynamic discovery of resources and extensibility and loose coupling are attained. To illustrate this framework, two new learning algorithms are introduced and implemented as services. The first is a data structure suitable for proximity queries over large datasets of low intrinsic dimension. The other uses a random projection to carry out novelty detection over high dimensional datasets.
APA, Harvard, Vancouver, ISO, and other styles
10

Sandhu, Raghbir Singh. "Intelligent spatial decision support systems." Thesis, University College London (University of London), 1998. http://discovery.ucl.ac.uk/1317911/.

Full text
Abstract:
This thesis investigates the conceptual and methodological issues for the development of Intelligent Spatial Decision Support Systems (ISDSS). These are spatial decision support systems (SDSS) integrating intelligent systems techniques (Genetic Algorithms, Neural Networks, Expert Systems, Fuzzy Logic and Nonlinear methods) with traditional modelling and statistical methods for the analysis of spatial problems. The principal aim of this work is to verify the feasibility of heterogeneous systems for spatial decision support derived from a combination of traditional numerical techniques and intelligent techniques in order to provide superior performance and functionality to that achieved through the use of traditional methods alone. This thesis is composed of four distinct sections: (i) a taxonomy covering the employment of intelligent systems techniques in specific applications of geographical information systems and SDSS; (ii) the development of a prototype ISDSS; (iii) application of the prototype ISDSS to modelling the spatiotemporal dynamics of high technology industry in the South-East of England; and (iv) the development of ISDSS architectures utilising interapplication communication techniques. Existing approaches for implementing modelling tools within SDSS and GIS generally fall into one of two schemes - loose coupling or tight coupling - both of which involve a tradeoff between generality and speed of data interchange. In addition, these schemes offer little use of distributed processing resources. A prototype ISDSS was developed in collaboration with KPMG Peat Marwick's High Technology Practice as a general purpose spatiotemporal analysis tool with particular regard to modelling high technology industry. The GeoAnalyser system furnishes the user with animation and time plotting tools for observing spatiotemporal dynamics; such tools are typically not found in existing SDSS or GIS. Furthermore, GeoAnalyser employs the client/server model of distributed computing to link the front end client application with the back end modelling component contained within the server application. GeoAnalyser demonstrates a hybrid approach to spatial problem solving - the application utilises a nonlinear model for the temporal evolution of spatial variables and a genetic algorithm for calibrating the model in order to establish a good fit for the dataset under investigation. Several novel architectures are proposed for ISDSS based on existing distributed systems technologies. These architectures are assessed in terms of user interface, data and functional integration. Implementation issues are also discussed. The research contributions of this work are four-fold: (i) it lays the foundation for ISDSS as a distinct type of system for spatial decision support by examining the user interface, performance and methodological requirements of such systems; (ii) it explores a new approach for linking modelling techniques and SDSS; (iii) it investigates the possibility of modelling high technology industry; and (iv) it details novel architectures for ISDSS based on distributed systems.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Decision support systems Australia"

1

Information, Decision, and Control (2007 Adelaide, Australia). 2007 Information Decision and Control (IDC): Adelaide, Australia, 12-14 February 2007. Piscataway, NJ: IEEE, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Information, Decision, and Control (2007 Adelaide, Aust.). 2007 Information Decision and Control (IDC): Adelaide, Australia, 12-14 February 2007. Piscataway, NJ: IEEE, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Information, Decision, and Control (2007 Adelaide, Aust.). 2007 Information Decision and Control (IDC): Adelaide, Australia, 12-14 February 2007. Piscataway, NJ: IEEE, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Information, Decision, and Control (2007 Adelaide, Aust.). 2007 Information Decision and Control (IDC): Adelaide, Australia, 12-14 February 2007. Piscataway, NJ: IEEE, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Australian Data Fusion Symposium (2nd 1999 Adelaide, Australia). IDC-99: 1999 Information, Decision and Control : Data and Information Fusion Symposium, Signal Processing and Communications Symposium and Decision and Control Symposium : Adelaide, Australia, 8-10 February, 1999 : proceedings. Piscataway, N.J: IEEE, 1999.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Loucks, Daniel P., and João R. da Costa, eds. Decision Support Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Moreno-Jiménez, José María, Isabelle Linden, Fatima Dargam, and Uchitha Jayawickrama, eds. Decision Support Systems X: Cognitive Decision Support Systems and Technologies. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46224-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Davis, Michael W. Applied decision support. Englewood Cliffs, N.J: Prentice Hall, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

IMACS/IFORS, International Colloquium on Managerial Decision Support Systems and Knowledge Based Systems (1st 1987 Manchester England). Managerial decision support systems. Amsterdam: North-Holland, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Introducing decision support systems. Oxford, UK: NCC Blackwell, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Decision support systems Australia"

1

Holzbecher, Ekkehard, Ahmed Hadidi, Nicolette Volp, Jeroen de Koning, Humaid Al Badi, Ayisha Al Khatri, and Ahmed Al Barwani. "Advanced Tools for Flood Management: An Early Warning System for Arid and Semiarid Regions." In Natural Disaster Science and Mitigation Engineering: DPRI reports, 209–23. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_7.

Full text
Abstract:
AbstractTechnologies concerning integrated water resources management, in general, and flood management, in particular, have recently undergone rapid developments. New smart technologies have been implemented in every relevant sector and include hydrological sensors, remote sensing, sensor networks, data integration, hydrodynamic simulation and visualization, decision support and early warning systems as well as the dissemination of information to decision-makers and the public. After providing a rough review of current developments, we demonstrate the operation of an advanced system with a special focus on an early warning system. Two case studies are covered in this chapter: one specific urban case located in the city of Parrametta in Australia in an area that shows similar flood characteristics to those found in arid or semiarid regions and one case regarding the countrywide Flash Flood Guidance System in Oman (OmanFFGS).
APA, Harvard, Vancouver, ISO, and other styles
2

Salles, Maryse. "Decision Support Systems." In Decision-Making and the Information System, 43–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119102663.ch2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Zopounidis, Constantin, and Michael Doumpos. "Decision Support Systems." In Intelligent Decision Aiding Systems Based on Multiple Criteria for Financial Engineering, 37–82. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4663-4_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Crossland, Martin D. "Decision Support Systems." In Encyclopedia of GIS, 1. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_269-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Walterscheid, Heinz. "Decision Support Systems." In Effektivität computergestützter Management-Entscheidungsprozesse, 21–59. Wiesbaden: Deutscher Universitätsverlag, 1996. http://dx.doi.org/10.1007/978-3-322-97723-6_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Filip, Florin Gheorghe, Constantin-Bălă Zamfirescu, and Cristian Ciurea. "Decision Support Systems." In Automation, Collaboration, & E-Services, 31–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47221-8_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Smith, William. "Decision Support Systems." In Systems Building with Oracle, 376–407. London: Macmillan Education UK, 2004. http://dx.doi.org/10.1007/978-0-230-00094-0_16.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Crossland, Martin D. "Decision Support Systems." In Encyclopedia of GIS, 460. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-17885-1_269.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Crossland, Martin D. "Decision Support Systems." In Encyclopedia of GIS, 232. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_269.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

French, Simon. "Decision Support Systems." In e-Democracy, 65–82. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9045-4_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Decision support systems Australia"

1

Elmahdi, A., and D. McFarlane. "A decision support system for sustainable groundwater management. Case study: Gnangara sustainability strategy – Western Australia." In WATER RESOURCES MANAGEMENT 2009. Southampton, UK: WIT Press, 2009. http://dx.doi.org/10.2495/wrm090301.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Ameliana and Windarto. "Implementation of Weighted Product Method in the Decision Support System of University Selection in Australia." In International Conference on IT, Communication and Technology for Better Life. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0008929400610070.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Zheng, M. M., and S. M. Krishnan. "Decision support by fusion in endoscopic diagnosis." In ANZIIS 2001. Proceedings of the Seventh Australian and New Zealand Intelligent Information Systems Conference. IEEE, 2001. http://dx.doi.org/10.1109/anziis.2001.974059.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bonner, James, and Clinton J. Woodward. "On domain-specific decision support systems for e-sports strategy games." In the 24th Australian Computer-Human Interaction Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2414536.2414544.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Barzi, Mohammad, and Ewen Siu Ming Sze. "Optimising the Jansz-Io Trunkline Next Project Using Integrated Production Modelling." In SPE Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/210655-ms.

Full text
Abstract:
Abstract The Chevron-operated Gorgon asset is the largest single resource project in Australia, with a portfolio of offshore gas fields to supply gas via two trunklines (Gorgon and Jansz-Io) to a three-train, 15.6 MTPA LNG plant and a 300 TJ/D domestic gas plant on Barrow Island. Gorgon will be a legacy project, with decades of production anticipated from the development of backfill fields gas resources. To realise the value of the asset, it is critical to select the right projects and execute them at the right time. Greater Gorgon Integrated Production Modelling (IPM) has been developed by Chevron Australia's gas supply team on behalf of the Gorgon Joint Venture (Australian Subsidiaries of Chevron, ExxonMobil, Shell, Osaka Gas, Tokyo Gas and JERA) to specifically enable optimisation of both the subsurface and surface value chain. It integrates reservoirs, wells, and subsea production networks to enable rigorous assessment of various portfolio-level development and planning scenarios. The focus of this paper is on the Jansz-Io trunkline, which is initially supplied by the massive depletion drive Jansz-Io field, and the key decision of how to maintain production post development of the Gorgon Stage 2 (GS2) project. To inform this key decision, extensive evaluation was conducted using coupled INTERSECT (IX) IPM model to assess Jansz-Io Compression (J-IC) concepts (floating platform vs subsea compression). The IX-IPM model includes either detailed IX dynamic simulation or simplified material balance (MBAL) reservoirs, and a detailed production system that captures the full pressure hydraulics and their complex interactions. Using this IX-IPM model, a systematic staircase approach was applied, starting with a minimum facility concept, before sequentially adding more functionalities (power, capacity, phasing and backfill fields tie-in) and quantifying their incremental benefits. This enabled comprehensive understanding of the compression model's pressure hydraulic performance and various value trade-offs at each step. A fit-for-purpose, fixed power compression model was implemented to commence the staircase assessment. Once subsea compression was selected, and as the assessment matured, vendor compressor performance curves were adopted for more rigorous modelling. Overall, the Greater Gorgon coupled IX-IPM model has proved to be invaluable in the assessment of the J-IC concept select and supported the Final Investment Decision (FID) on J-IC in 2021. The coupled IX-IPM model is continually refined with greater engineering resolution and additional production history to support the wider Gorgon asset decisions.
APA, Harvard, Vancouver, ISO, and other styles
6

Lambert, Jamie, Melanie Bok, and Azivy Aziz. "Integrating Underwater Data into GIS for Offshore Decommissioning in Bass Strait, Australia." In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205823-ms.

Full text
Abstract:
Abstract Through asset lifecycle, data is collected for a variety of purposes across multiple disciplines, and exists in various formats and repositories. Decommissioning projects utilize and repurpose a multitude of these datasets; from use in analysis and planning, to facilitating systematic environmental assessments, and meaningful discussion with stakeholders. The key challenge is how do we consolidate historical data, incorporate new data, and make it evergreen to support planning and informed decision making; and how do we coordinate large volumes of previously disparate data in a meaningful way for all users with a simple access model? A team of geographic information system (GIS) practitioners and subject matter contacts in technical and health, safety and environment (HSE) disciplines was convened to collect, sort, and compile known historical offshore data, including, but not limited to; pipeline and structural inspections and environmental studies, all captured via Remote Operated Vehicle (ROV), Side Scan Sonar (SSS), and sampling programs. Data was reformatted to standardize headers and attributes allowing for merging of existing like-data and to support new data integration. To this end, we also worked collaboratively with vendors to optimize data collection and improve alignment with our internal data structures. The Esri GIS technology was utilized for data integration, specifically the web and mobile environments. Through these environments, non-GIS users could easily access data and focused applications, supporting ease of data visualization and allowing for a single view of data spanning decades and covering multiple themes. This enabled an enhanced understanding of the offshore environment, allowing us to identify gaps and focus areas for future data capture, helping to facilitate cross-discipline discussions, and identification of operational synergies; improving access, efficiency, and reducing decommissioning costs. Data integration resulting from this initiative and delivery through a spatially aware GIS environment is providing unprecedented access to a vast scope of cross-disciplinary data previously not possible with more traditional engineering methods and data formats. Data accessibility aids communication, and when combined with early engagement across multi-disciplinary teams, the path to decision making is reduced, synergies gained, and costs are reduced through improved efficiency and optimization.
APA, Harvard, Vancouver, ISO, and other styles
7

Xie, Shuiwei, and Warren F. Smith. "Towards a Hybrid Solver: Integration of a Genetic Algorithm Within “DSIDES”." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34400.

Full text
Abstract:
In contributing to the body of knowledge for decision-based design, the work reported in this paper has involved steps towards building a hybrid genetic algorithm to address systems design. Highlighted is a work in progress at the Australian Defence Force Academy (ADFA). A genetic algorithm (GA) is proposed to deal with discrete aspects of a design model (e.g., allocation of space to function) and a sequential linear programming (SLP) method for the continuous aspects (e.g., sizing). Our historical Decision Based Design (DBD) tool has been the code DSIDES (Decision Support In the Design of Engineering Systems). The original functionality of DSIDES was to solve linear and non-linear goal programming styled problems using linear programming (LP) and sequential (adaptive) linear programming (SLP/ALP). We seek to enhance DSIDES’s solver capability by the addition of genetic algorithms. We will also develop the appropriate tools to deal with the decomposition and synthesis implied. The foundational paradigm for DSIDES, which remains unchanged, is the Decision Support Problem Technique (DSPT). Through introducing genetic algorithms as solvers in DSIDES, the intention is to improve the likelihood of finding the global minimum (for the formulated model) as well as the ability of dealing more effectively with nonlinear problems which have discrete variables, undifferentiable objective functions or undifferentiable constraints. Using some numerical examples and a practical ship design case study, the proposed GA based method is demonstrated to be better in maintaining diversity of populations, preventing premature convergence, compared with other similar GAs. It also has similar effectiveness in finding the solutions as the original ALP DSIDES solver.
APA, Harvard, Vancouver, ISO, and other styles
8

Karidis, Antonis E. "Integrated Decision Support Environments in Distributed High-End Audio-Visual Content Creation: The Use of High Performance Computing and Networking." In SMPTE Australia Conference. IEEE, 1999. http://dx.doi.org/10.5594/m001228.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Chen, Man-kuen S., Chui-fat C. Chau, and Waldo C. Kabat. "Decision support systems." In the 1985 ACM annual conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/320435.320586.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Loyko, A. O., and S. A. Gusev. "Decision Support Systems." In the 2019 10th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3345035.3345081.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Decision support systems Australia"

1

Sorensen, H. B., John S. Park, and Jr. Instructional Systems Development Decision Support. Fort Belvoir, VA: Defense Technical Information Center, November 1990. http://dx.doi.org/10.21236/ada228052.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Grevet, Jean-Louis M., and Alexander H. Levis. Coordination in Organizations with Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, July 1988. http://dx.doi.org/10.21236/ada197951.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Gurney, John O., Marsh Jr., Wauchope Elaine, and Kenneth. Focus of Attention in Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, May 1995. http://dx.doi.org/10.21236/ada294037.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bostick, K. V. Decision support system to select cover systems. Office of Scientific and Technical Information (OSTI), February 1995. http://dx.doi.org/10.2172/10116819.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Hawgood, John. Formal 'Systems Languages' in Decision Support Systems for Military Commanders. Fort Belvoir, VA: Defense Technical Information Center, June 1986. http://dx.doi.org/10.21236/ada169673.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kennedy, John C., Piyush Sabharwall, Shannon M. Bragg-Sitton, Konor L. Frick, Patrick McClure, and D. V. Rao. Special Purpose Application Reactors: Systems Integration Decision Support. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1475413.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Hirsch, Gary B., Jack Homer, Brooke N. Chenoweth, George A. Backus, and David R. Strip. Behavior-aware decision support systems : LDRD final report. Office of Scientific and Technical Information (OSTI), November 2007. http://dx.doi.org/10.2172/934860.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Mowrer, H. Todd, Klaus Barber, Joe Campbell, Nick Crookston, Cathy Dahms, John Day, Jim Laacke, et al. Decision support systems for ecosystem management: An evaluation of existing systems. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1997. http://dx.doi.org/10.2737/rm-gtr-296.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Smirnov, Alexander, Tatiana Levashova, Nikolay Teslya, and Michael Pashkin. Decision Support in Socio-cyber-physical Systems: Conceptual Framework and Decision Making Stages. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, October 2019. http://dx.doi.org/10.7546/crabs.2019.10.10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Riedel, Sharon L. User Acceptance and Field Implementation of Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, May 1988. http://dx.doi.org/10.21236/ada200412.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Decision support systems Australia' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography