Australian agriculture is one area in which a number of intelligent support systems have been developed. It appears, however, that comparatively few of these systems are widely used or have the impact the developers might have wished. In this study a possible explanation for this state of affairs was investigated. The development process for 66 systems was examined. Particular attention was paid to the nature of user involvement, if any, during development and the relationship to system success. The issue is not only whether there was user involvement but rather the nature of the involvement, that is, the degree of influence users had during development. The patterns identified in the analysis suggest user influence is an important contributor to the success of a system. These results have theoretical significance in that they add to knowledge of the role of the user in the development of intelligent support systems. The study has drawn together work from three areas: Rogers’ diffusion theory, the technology acceptance model, and theories relating to user involvement in the development of information systems. Most prior research in the information systems area has investigated one or two of the above three areas in any one study. The study synthesizes this knowledge through applying it to the field of intelligent support systems in Australian agriculture. The results have considerable practical significance, as apparently developers of intelligent support systems in Australian agriculture do not recognize the importance of user participation, and continue to develop systems with less than optimum impact.

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Thesis (Ph.D. (Geography and Environmental Studies))--North-West University, Potchefstroom Campus, 2007.

Introduction Organizations are exposed to a rapidly changing business environment with never ending challenges. Investments in information technology (IT) have been one common approach to support organizations. Business Intelligence (BI), an off-spring from IT, is a system that assists many organizations in taking more accurate and timely decisions, improving process monitoring and providing better support for decision making. Recently organizations have started to realize the value of investing in BI, by discovering its analytical methods and capabilities to create business value. Problem Investments in BI have increased substantially over the past years and one reason for this might be due to vendors praise about BI’s ability to deliver business value. Significantly increased business value, better decision making, and high returns on investments are only a few benefits that have been claimed for. When considering the fact that it is very difficult to measure any direct benefits from IT investments in general, and BI as a consequence, an interest for analyzing the arguments used for selling BI emerged. Purpose The purpose of this thesis is to identify what arguments vendors and suppliers use when selling BI solutions, and explore their value by analyzing them through the use of existing theories from literature. Method A qualitative approach has been adopted, where unstructured interviews with BI vendors and suppliers were conducted. An inductive approach has been applied to gather arguments and then shifted to a deductive, in order to finalize the study and analyze arguments with appropriate theory. The research has been performed from without the Swedish market with well-known organizations. Conclusions A single version of the truth, control, and time savings are credible arguments for investing in BI. Furthermore, cost savings and improved analytical capabilities are fairly credible, whereas increased efficiency has least credibility when analyzed against theories. In general, we believe that the ability to gain from these positive effects from BI, organizations have to take an active role in realizing these.

Persistent conflicts between stakeholders and complex trade offs among forest values have created a difficult decision environment for sustainable forest management. Tools developed for decision support in land use planning are essential for managing these challenges. This research study is an interactive assessment of a land use planning Decision Support Tool (DST) in the Invermere Timber Supply Area (TSA), located in the East Kootenay area of British Columbia. The aim of this study is to explore whether stakeholders' initial stated preferences change and whether trade-offs are made between various forest values upon observation of a long-term forecast of these values using a DST. Representatives from various stakeholder groups in the area were assembled for individual sessions to interact with the multi-criteria DST. Participants were required to state their preferences for six forest values using a weighting scheme. The DST developed an output for each forest value based on the participants' preferences. Upon review of the DST output, the participant had the opportunity to alter their initial preferences iteratively until a desirable output was found. The results indicate that participants' preferences changed after reviewing the DST outputs and that participants are willing to make trade-offs between various forest values using a DST to find a desirable solution. However, the preference order of the forest values changed only slightly from the participants' initial to preferred scenarios; instead participants made drastic changes to the weighting of each value to find a desirable output. Participants also stated their willingness to use DSTs for land use planning decision-making, although underlying assumptions built into the model must be improved before stakeholders can trust the tool as an aid for decision-making. Studies such as this can further the development of DSTs to help find desirable decisions for sustainable resource management and to help create a productive and engaging process.

In this thesis, the decision analysis process of investigating the best optimal strategy for Tehran water management in 2021 is described. Such process is normally divided into four steps including: structuring the problem; identifying feasible strategies, their impact and uncertainty; quantifying preferences; and evaluation of countermeasures and sensitivity analysis. Here, in order to structure the problem, the characteristics of Tehran with respect to water issues and its history of water management are reviewed. The state of surface waters and ground waters and a description of Tehran plan for waste water treatment are given, the most significant constraints of Tehran water sector are classified and the challenges of climate change and variability are explained. The feasible adaptation strategies are designed subsequently based on that classification, data extracted from a survey and a number of interviews with water officials and managers and ordinary citizens in Tehran. Each strategy contains a series of separate measures with different weights. The phase of quantifying preferences and elucidating utility functions is conducted based on the data available from previous studies and also the current survey. The measures include: installing water saving devices, awareness raising to change citizens’ water consumption pattern, adding new sources of surface water, investing on waste water utilization, migration control and repairing water distribution network.Different combinations of these measures provide different possibilities for formulating adaptation strategies. We compare two more discussed adaptation strategies of the spectrum of strategies; one is inclined toward exploiting more water resources while the other one is more focused on demand management. The former is mainly supported by water officials and the latter advocated by water experts we interviewed. The criteria of comparison are social acceptability, economic feasibility, time-efficiency and environmental tenability. By considering the uncertainty attributed to the criteria weights, the WEB-HIPRE DSS analysis shows that the demand-oriented strategy is the optimal one in most cases, however, if time-efficiency and/or economic feasibility gain very high significance, the strategy of water officials wins over that of experts.

New or improved decision analysis tools are developed in this thesis to address strategic policy analysis with specific focus on two topics: strategic conflict analysis and region-performance comparisons. A strategic conflict refers to a situation in which two or more decision makers (DMs) are to make a decision that affects issues over which they have different preferences. Various forms of strategic conflict exist all around us, in areas such as environmental management, international relations, economic competition, and relationships among individuals. The graph model for conflict resolution (GMCR) is an advanced and comprehensive tool to systematically study strategic conflicts. A well-known decision tool, the analytic network process (ANP) is adapted for use in strategic conflict analysis and a comparison of the performance of ANP with GMCR is carried out. Both methods are applied to an international trading conflict between the United States and China over the importation of television sets into the US in order to gain strategic insights about this dispute using the two different but complementary approaches. A country's overall performance comparison with respect to different kinds of indices such as economic, environmental and political indices constitutes another interesting topic for strategic policy analysis. An index aggregation approach is proposed to compare BRICSAM countries, a populous rapidly-growing economic group of nations consisting of Brazil, Russia, India, China, South Africa, ASEAN (Association of South-East Asian Nations), and Mexico with G7 (Group of Seven), the most developed country club including Canada, France, Italy, Japan, Germany, United Kingdom and the United States. A data-envelopment-analysis (DEA) based approach is proposed to aggregate different ranking indices for BRICSAM and the G7 countries. The proposed method can provide a fair overall assessment of a country's standing by maximizing its possibility of obtaining the best evaluation score. Finally, a framework to carry out generic strategic analysis for regions' competence analysis is designed based upon the theory of generic strategic analysis proposed by Porter (1980). This is a well-known approach for use in business competence analysis. The basic idea is to carry out generic strategic analysis in policy studies and two decision tools, DEA and the analytic hierarchy process, are employed to quantify the analysis of competence efficiency and potentiality, respectively. A case study of the competence analysis of provinces in China is used to demonstrate the analysis procedure.

Most companies relying on an Information Technology (IT) system for their daily operations heavily invest in its maintenance. Tools that monitor network traffic, record anomalies and keep track of the changes that occur in the system are usually used. Root cause analysis and change impact analysis are two main activities involved in the management of IT systems. Currently, there exists no universal model to guide analysts while performing these activities. Although the Information Technology Infrastructure Library (ITIL) provides a guide to the or- ganization and structure of the tools and processes used to manage IT systems, it does not provide any models that can be used to implement the required features. This thesis focuses on providing simple and effective models and processes for root cause analysis and change impact analysis through mining useful artifacts stored in a Confguration Management Database (CMDB). The CMDB contains information about the different components in a system, called Confguration Items (CIs), as well as the relationships between them. Change reports and incident reports are also stored in a CMDB. The result of our work is the Decision support for Root cause Analysis and Change impact Analysis (DRACA) framework which suggests possible root cause(s) of a problem, as well as possible CIs involved in a change set based on di erent proposed models. The contributions of this thesis are as follows: - An exploration of data repositories (CMDBs) that have not been previously attempted in the mining software repositories research community. - A causality model providing decision support for root cause analysis based on this mined data. - A process for mining historical change information to suggest CIs for future change sets based on a ranking model. Support and con dence measures are used to make the suggestions. - Empirical results from applying the proposed change impact analysis process to industrial data. Our results show that the change sets in the CMDB were highly predictive, and that with a confidence threshold of 80% and a half life of 12 months, an overall recall of 69.8% and a precision of 88.5% were achieved. - An overview of lessons learned from using a CMDB, and the observations we made while working with the CMDB.

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New or improved decision analysis tools are developed in this thesis to address strategic policy analysis with specific focus on two topics: strategic conflict analysis and region-performance comparisons. A strategic conflict refers to a situation in which two or more decision makers (DMs) are to make a decision that affects issues over which they have different preferences. Various forms of strategic conflict exist all around us, in areas such as environmental management, international relations, economic competition, and relationships among individuals. The graph model for conflict resolution (GMCR) is an advanced and comprehensive tool to systematically study strategic conflicts. A well-known decision tool, the analytic network process (ANP) is adapted for use in strategic conflict analysis and a comparison of the performance of ANP with GMCR is carried out. Both methods are applied to an international trading conflict between the United States and China over the importation of television sets into the US in order to gain strategic insights about this dispute using the two different but complementary approaches. A country's overall performance comparison with respect to different kinds of indices such as economic, environmental and political indices constitutes another interesting topic for strategic policy analysis. An index aggregation approach is proposed to compare BRICSAM countries, a populous rapidly-growing economic group of nations consisting of Brazil, Russia, India, China, South Africa, ASEAN (Association of South-East Asian Nations), and Mexico with G7 (Group of Seven), the most developed country club including Canada, France, Italy, Japan, Germany, United Kingdom and the United States. A data-envelopment-analysis (DEA) based approach is proposed to aggregate different ranking indices for BRICSAM and the G7 countries. The proposed method can provide a fair overall assessment of a country's standing by maximizing its possibility of obtaining the best evaluation score. Finally, a framework to carry out generic strategic analysis for regions' competence analysis is designed based upon the theory of generic strategic analysis proposed by Porter (1980). This is a well-known approach for use in business competence analysis. The basic idea is to carry out generic strategic analysis in policy studies and two decision tools, DEA and the analytic hierarchy process, are employed to quantify the analysis of competence efficiency and potentiality, respectively. A case study of the competence analysis of provinces in China is used to demonstrate the analysis procedure.