Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

PRAGMATIST ECOLOGICAL ECONOMICS: FOCUSING ON HUMAN-NATURE RELATIONSHIPS AND SOCIAL-ECOLOGICAL SYSTEMS

I propose pragmatist philosophy as a companion for ecological economics, a research tradition with a focus on addressing sustainability issues and integrating ecological principles, economics, and the broader social sciences. Ecological economics laudable goals include balancing competing values, tradeoffs, and insights for more equitable decision-making. However, the field is built upon somewhat tenuous philosophical and theoretical foundations, which has resulted in a muddled body of literature, concerns about relativistic science, and questions about the future viability of the field. To address such concerns, I propose and articulate pragmatist ecological economics. Generally, joining pragmatism and ecological economics provides established beliefs about: the nature of reality with a contextual ontology; the way we learn via Dewey’s experience model; the way to assess knowledge based upon deliberative democracy and ‘wary assessment’ and; a clear purpose to communicate, understand, and facilitate social learning about the human-nature relationship. Specific recommendations include a core subject matter (a comprehensive understanding of human-nature relationships), integration of normative sustainability, and a focus on better processes and methods that synthesize across big ideas (e.g., relationship to place research, ecosystem services). I stress that all approaches to understanding the human-nature relationship provide different, partial understandings. Consequently, I demonstrate a ‘research menu’ framework by weighing into a methodological debate between Q- and R-methodology. Finally, I propose that a social-ecological systems perspective and a pragmatist ecological economics are compatible, as the former can help the latter better achieve its applied goals by orienting the understanding of the human-nature relationships within the larger system

Mining climate data for shire level wheat yield predictions in Western Australia

Climate change and the reduction of available agricultural land are two of the most important factors that affect global food production especially in terms of wheat stores. An ever increasing world population places a huge demand on these resources. Consequently, there is a dire need to optimise food production. Estimations of crop yield for the South West agricultural region of Western Australia have usually been based on statistical analyses by the Department of Agriculture and Food in Western Australia. Their estimations involve a system of crop planting recommendations and yield prediction tools based on crop variety trials. However, many crop failures arise from adherence to these crop recommendations by farmers that were contrary to the reported estimations. Consequently, the Department has sought to investigate new avenues for analyses that improve their estimations and recommendations. This thesis explores a new approach in the way analyses are carried out. This is done through the introduction of new methods of analyses such as data mining and online analytical processing in the strategy. Additionally, this research attempts to provide a better understanding of the effects of both gradual variation parameters such as soil type, and continuous variation parameters such as rainfall and temperature, on the wheat yields. The ultimate aim of the research is to enhance the prediction efficiency of wheat yields. The task was formidable due to the complex and dichotomous mixture of gradual and continuous variability data that required successive information transformations. It necessitated the progressive moulding of the data into useful information, practical knowledge and effective industry practices. Ultimately, this new direction is to improve the crop predictions and to thereby reduce crop failures. The research journey involved data exploration, grappling with the complexity of Geographic Information System (GIS), discovering and learning data compatible software tools, and forging an effective processing method through an iterative cycle of action research experimentation. A series of trials was conducted to determine the combined effects of rainfall and temperature variations on wheat crop yields. These experiments specifically related to the South Western Agricultural region of Western Australia. The study focused on wheat producing shires within the study area. The investigations involved a combination of macro and micro analyses techniques for visual data mining and data mining classification techniques, respectively. The research activities revealed that wheat yield was most dependent upon rainfall and temperature. In addition, it showed that rainfall cyclically affected the temperature and soil type due to the moisture retention of crop growing locations. Results from the regression analyses, showed that the statistical prediction of wheat yields from historical data, may be enhanced by data mining techniques including classification. The main contribution to knowledge as a consequence of this research was the provision of an alternate and supplementary method of wheat crop prediction within the study area. Another contribution was the division of the study area into a GIS surface grid of 100 hectare cells upon which the interpolated data was projected. Furthermore, the proposed framework within this thesis offers other researchers, with similarly structured complex data, the benefits of a general processing pathway to enable them to navigate their own investigations through variegated analytical exploration spaces. In addition, it offers insights and suggestions for future directions in other contextual research explorations

Making viability sustainable

Conventionally, the neoclassical economic discourse is used to interpret sustainability. Sustainability is regarded as an economic problem and sustainability policies focus on maintaining various forms of capital. This approach is conceptually inadequate and it is unable to recognise or correct systemic non‐sustainability that perpetuates unsustainable behaviour.This thesis challenges the epistemological authority of neoclassical economics as being an appropriate policy framework for creating effective sustainability policy.The extent, significance and persistence of sustainability issues suggest thatremediation is beyond the capacity of conventional policy approaches. The newunderstandings of complexity and uncertainty make new conceptual andmethodological demands on policy makers. The dominance and intransigence ofthe neoclassical economic episteme means that changes towards sustainability aremore than simple reform processes; conceptual and cognitive change is needed.This thesis suggests that economics needs to be, and can be, reconceptualised and reframed within a sustainability‐informed ontology that includes economic, social, cultural and ecological layers. It describes a Viability Analysis framework that accommodates pluralist, multidimensional viability constructs. It proposes a sustainability‐informed system of national accounts in which economic activity is recalibrated with qualitative data within a reconceptualised sustainability‐informed taxonomy of categories. The sustainability‐informed system of national accounts provides policy makers and businesses with information that can be used to steer economic activity towards sustainability paths. Using an opt‐in approach, businesses can qualify for lower tax rates by demonstrating their movement towards sustainability. By framing economics within a sustainability‐informed ontology and accounting narrative, a symbiosis between economics and sustainability is possible so that sustainable behaviour can be economically viable, and economic viability can be sustainable

Knowledge-Based Decision Support for Integrated Water Resources Management with an application for Wadi Shueib, Jordan

This book takes a two-staged approach to contribute to the contemporary Integrated Water Resources Management (IWRM) research. First it investigates sub-basin-scale IWRM modelling and scenario planning. The Jordanian Wadi Shueib is used as exemplary case study. Then, it develops a framework to collaboratively manage planning and decision making knowledge on the basis of semantic web technologies. Future IWRM initiatives can benefit from the valuable insights achieved in the presented study

Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

Valuing adaptation under rapid change

AbstractThe methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change.Please cite this report as: Jones, RN, Young, CK, Handmer, J, Keating, A, Mekala, GD, Sheehan, P 2013 Valuing adaptation under rapid change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 192.The methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change

A BUSINESS MODEL FOR SUSTAINABLE SMME PIG FARMING IN THE CENTRAL FREE STATE OF SOUTH AFRICA

Published ThesisThe lack of a reliable organisational approach and dearth of knowledge regarding a more effective business model resulted in cases of phenomenal business failures amongst pig farming SMMEs in the Central Free State Province of South Africa, as empirical evidence show. Therefore, this study develops a Commonage Cooperative Model (CCM) to enhance consistency in performance and sustainability. It expounds on the economics of scale derived through resourcing amongst the alliances of wider stakeholders. Hence, it advances existing models in agribusiness-related strategic management that supports Local Economic Development (LED). Being driven by the government policies on cooperative development, the model encompasses a value chain of small-scale pig farming SMMEs that can cooperate to improve competition. A sequential application of questionnaire survey and interview approaches was used on 144 pig farming SMMEs across 4 district municipalities and 1 metro. Results justified the acceptance of 4 hypotheses and rejection of 9 others. Findings were based on marketing management activities, innovation management activities, performance and sustainability, and agricultural background of the Province. All null hypotheses were tested to determine if a number of variables were significantly associated with performance and sustainability. H01 was rejected when test results revealed that there was no significant association in terms of sales growth, and return-on-investment over the past 5 years. Regarding size of operation in terms of enterprise’s gross profit (before tax) over the past 1-5 years, the null hypothesis was accepted. H02 was rejected when test results indicated that, with respect to enterprise diversification as well as enterprise indebtedness, significant associations existed between these variables and performance and sustainability. Existing marketing strategies had a significant impact on the performance and sustainability amongst the pig farming SMMEs; hence, H03 was rejected when results revealed that there was no significant association. H04 was rejected when test results indicated that there was a significant association between increasing partners of the business and enterprise performance and sustainability. H05 was rejected when test results showed that there was a significant association between the use of services of government Agricultural Extension Officers and performance and sustainability. H06 was rejected when test results showed that there was a significant association between innovation management activities and enterprise performance and sustainability. H07 was accepted when results indicated that there was no significant association between size categories and enterprise indebtedness. H08 was accepted given that there was no significant association between form of a business organization and enterprise current indebtedness. H09 was accepted based on test results indicating that there was no significant association between current life cycle stage and enterprises currently indebted amongst pig farming SMMEs in the Central Free State. The implications of these results are that the pig farming SMMEs need to adapt to a redefined and result-oriented organisational approach that increases their capabilities in the livestock business. Hence, the Commonage Cooperative Model promotes collective risk and diversity, which was lacking amongst the majority of them, and low resource commitment affected capabilities in many ways. Future research is recommended concerning the dynamics of parameter changes in the model

Syntactic and Semantic Interoperability Among Hydrologic Models

Development of integrated hydrologic models requires coupling of multidisciplinary, independent models and collaboration between different scientific communities. Component-based modeling provides an approach for the integration of models from different disciplines. A key advantage of component-based modeling is that it allows components to be created, tested, reused, extended, and maintained by a large group of model developers and end users. One significant challenge that must be addressed in creating an integrated hydrologic model using a component-based approach is enhancing the interoperability of components between different modeling communities and frameworks. The major goal of this work is to advance the integration of water related model components coming from different disciplines using the information underlying these models. This is achieved through addressing three specific research objectives. The first objective is to investigate the ability of component-based architecture to simulate feedback loops between hydrologic model components that share a boundary condition, and how data is transfered between temporally misaligned model components. The second objective is to promote the interoperability of components across water-related disciplinary boundaries and modeling frameworks by establishing an ontology for components\u27 metadata. The third study objective is to develop a domain-level ontology for defining hydrologic processes