Approved for public release; distribution is unlimited / scheduling solutions for routing aircraft, crews and logistical support needed to successfully operate in this new environment. The opportunity exists for the DoD's private aircraft operation, the Joint Operational Support Airlift Center (JOSAC), to utilize some of the same system features used in commercial operations such as NetJets to improve operations. This thesis will analyze the use of commercial air operator strategies and DSS's to be used in JOSAC to improve operational effectiveness. It will look to add new capabilities and processes used in commercial DSS's along with the implementation of the disruptive technology, microjets. Some of the potential benefits include improved operational performance, solutions to scheduling inefficiencies and improved mission readiness. With these improvements the potential for a military microjet operation in the future is a real possibility. / 1st Lieutenant, United States Air Force

A project report submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering Johannesburg, 1996 / Current practice of'the rural water sector in Mozambique does not generally consider all factors that have influenc.eon project sustainability, The urgent need to provide returnees in rural areas with safe water, does not give adequate time to engineers, technicians and those involved in the sector, to conceive and plan a water project property. A Decision Support System (DSS) for rural water supply has been proposed to assist the decision making process to be more systematic, fast and comprehensive. It requires a number of input cata variables which are not difficult to obtain and these variables have been selected to ensure that most aspects inherent in a successful project are considered. The main achievement of this system is the project report, similar to a project preliminary design, and the financial results which are important for project assessment and ranking. The Decision Support System is a computational model which uses engineering and economics approach to combine and process input data and information contained in its database. While the calculation method does not need constant updating, the database has to be verified frequently to produce reliable results. South African prices have been used in the database construction but a correction factor facility was incorporated to adjust and make the model useable in Mozambique. The model has been designed to be used by planners, engineers and technicians, and funding agencies. The model can be used by planners to assess implication of policy decisions on future water supplies and water resources development. For engineers and technicians, the model estimates water demands, project components sizes and quantities, and water source development and reliability. To funding agencies, the model is a tool to determine the best investment scenario of a rural water supply project.

by Chan Kok-Wing, Chu Ming-Cheung. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1985. / Bibliography: leaves 100-102.

La facilitation est un élément central dans une prise de décision de groupe surtout en faisant l'usage des outils de nouvelle technologie. Le facilitateur, pour rendre sa tâche facile, a besoin des solutions de vote pour départager les décideurs afin d'arriver à des conclusions dans une prise de décision. Une procédure de vote consiste à déterminer à partir d’une méthode le vainqueur ou le gagnant d’un vote. Il y a plusieurs procédures de vote dont certaines sont difficiles à expliquer et qui peuvent élire différents candidats/options/alternatives proposées. Le meilleur choix est celui dont son élection est acceptée facilement par le groupe. Le vote dans la théorie du choix social est une discipline largement étudiée dont les principes sont souvent complexes et difficiles à expliquer lors d’une réunion de prise de décision. Les systèmes de recommandation sont de plus en plus populaires dans tous les domaines de science. Ils peuvent aider les utilisateurs qui n’ont pas suffisamment d’expérience ou de compétence nécessaires pour évaluer un nombre élevé de procédures de vote existantes. Un système de recommandation peut alléger le travail du facilitateur dans la recherche d’une procédure vote adéquate en fonction du contexte de prise de décisions. Le sujet de ce travail de recherche s’inscrit dans le champ de l’aide à la décision de groupe. La problématique consiste à contribuer au développement d’un système d’aide à la décision de groupe (Group Decision Support System : GDSS). La solution devra s’intégrer dans la plateforme logicielle actuellement développée à l’IRIT GRUS : GRoUp Support. / Facilitation is a central element in decision-making, especially when using new technology tools. The facilitator, to make his task easy, needs voting solutions to decide between decision-makers in order to reach conclusions in a decision-making process. A voting procedure consists of determining from a method the winner of a vote. There are several voting procedures, some of which are difficult to explain and which may elect different candidate/options/alternatives proposed. The best choice is the one whose election is easily accepted by the group. Voting in social choice theory is a widely studied discipline whose principles are often complex and difficult to explain at a decision-making meeting. Recommendation systems are becoming more and more popular in all fields of science. They can help users who do not have sufficient experience or competence to evaluate large numbers of existing voting procedures. A recommendation system can lighten the facilitator's workload in finding an appropriate voting procedure based on the decision-making context. The objective of this research work is to design such recommendation system. This work is in the field of group decision support. The issue is to contribute to the development of a Group Decision Support System (GDSS). The solution will have to be integrated into the software platform currently being developed at IRITGRUS: GRoUp Support.

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.

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.

Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these “intelligent” systems, increasing their acceptance as decision aids in industry has remained a formidable challenge. If intelligent systems are to be successful, and their full impact on decision-making performance realized, a greater understanding of the factors that influence recommendation acceptance from intelligent machines is needed. Through an empirical experiment in the financial services industry, this study investigated the effects of perceived behavioral similarity (similarity state) on the dependent variables of recommendation acceptance, decision performance and decision efficiency under varying conditions of uncertainty (volatility state). It is hypothesized in this study that behavioral similarity as a design element will positively influence the acceptance rate of machine recommendations by human users. The level of uncertainty in the decision context is expected to moderate this relationship. In addition, an increase in recommendation acceptance should positively influence both decision performance and decision efficiency. The quantitative exploration of behavioral similarity as a design element revealed a number of key findings. Most importantly, behavioral similarity was found to positively influence the acceptance rate of machine recommendations. However, uncertainty did not moderate the level of recommendation acceptance as expected. The experiment also revealed that behavioral similarity positively influenced decision performance during periods of elevated uncertainty. This relationship was moderated based on the level of uncertainty in the decision context. The investigation of decision efficiency also revealed a statistically significant result. However, the results for decision efficiency were in the opposite direction of the hypothesized relationship. Interestingly, decisions made with the behaviorally similar decision aid were less efficient, based on length of time to make a decision, compared to decisions made with the low-similarity decision aid. The results of decision efficiency were stable across both levels of uncertainty in the decision context.

<p>Introduction</p><p>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.</p><p>Problem</p><p>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.</p><p>Purpose</p><p>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.</p><p>Method</p><p>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.</p><p>Conclusions</p><p>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.</p>

Thesis (M.A.)--University of Wyoming, 2007. / Title from PDF title page (viewed on June 11, 2009). Includes bibliographical references (p. 82-89).

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2004. / Thesis advisor(s): Alex Bordetsky. Includes bibliographical references (p. 83-85). Also available online.