Dissertations / Theses on the topic 'Integrated Decision Framework (IDF)'

On the way towards a more biobased economy, the sustainable use of global wood resources remains a challenge as several trade-offs arise, e.g., from an increased energetic use of wood, an increased use of innovative but probably less recyclable wood composites, or from the need to conserve other forest ecosystem services. The aim of this study is to identify existing environmental indicators and methods for an evaluation of the sustainability of wood products in consideration of all life cycle stages, site-dependent aspects and later use in corporate decision-making. We chose a systematic literature review to answer the research questions explicitly and comprehensively. Qualitative content analysis was used to code indicators and scientific methods according to the Pressure-State-Response (PSR) framework. The sample (N = 118) is characterized by a high number of life cycle assessment (LCA) case studies. In 51% of all studies, the study authors use a combination of different methods. A total of 78 indicators and 20 site-dependent aspects could be identified in the sample. The study findings represent a first step towards a holistic environmental assessment of wood products.

The façade retrofit market faces some key barriers: the selection of performance criteria and the reliability of the performance data. On the demand side, the problem is approached from an investment perspective which creates "split incentives" between the stakeholders who pay for the investment and those who benefit from it. On the supply side, there is an inherent complexity in modeling these options because of the incomplete knowledge of the physical and cost parameters involved in the performance evaluation. The thermal comfort of the building occupant is an important component of the retrofit performance assessment. This research attempts to fill a gap in the approach to façade retrofit decision by 1) quantifying uncertainties in these three dimensions of performance, 2) incorporating new financing models available in the retrofit market, 3) considering the target and risk attitude of the decision maker. The methodology proposed in this research integrates key indicators for delivery process, environmental performance, and investment performance. The purpose is to provide a methodological framework for performance evaluation. A residential case study is conducted to test the proposed framework. Three retrofit scenarios including the financing structure are examined. Each façade retrofit scenario is then evaluated based on the level of confidence to meet or exceed a specific target improvement for the Net Present Value and the risk to fall below a minimum improvement threshold. The case study results confirm that risk must be considered for more reliable façade retrofit decision-making. Research findings point to further research needed to expand the understanding of the interdependencies among uncertain parameters.

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2002.
Includes bibliographical references (leaf 65).
by Micah T. Samuels.
S.M.

La desagregació de preferències pretén capturar models de preferències mitjançant la descomposició de la informació obtinguda a partir de preferències indirectes que estan en forma d'eleccions holístiques o judicis. Des d'una perspectiva d'ajuda a la presa de decisions multi criteri, aquesta informació es pren com a punt de partida en un procés d'inferència que condueix a model de preferències basat en punts de vista, generalment conflictius, que conjuntament formen una base per a la decisió. L'estudi de les decisions humanes ha rebut una atenció creixent en els últims anys des de diverses disciplines, que inclouen des de les ciències del comportament (anàlisi de decisions, desagregació de preferències), la intel·ligència artificial (aprenentatge de preferències), fins a l'economia i el màrqueting (teoria de l'elecció). Les tres corrents, encara que originades per diferents filosofies, convergeixen ràpidament cap a una comprensió integral de les preferències, que és l'element bàsic per a les decisions i accions humanes. Aquesta tesi doctoral aprofundeix en aquesta àrea de recerca mitjançant la introducció d'un marc analític integrat que permet capturar les preferències d'una forma complexa a partir de l'observació d'opcions holístiques, decisions i judicis.
La desagregación de preferencias pretende capturar modelos de preferencias mediante la descomposición de la información obtenida con preferencias indirectas que están en forma de elecciones holísticas o juicios. Desde una perspectiva de ayuda a la toma de decisiones multicriterio, dicha información se toma como punto de partida en un proceso de inferencia que conduce a modelo de preferencias basado en puntos de vista, generalmente conflictivos, que conjuntamente forman una base para la decisión. El estudio de las decisiones humanas ha recibido una atención creciente en los últimos años desde varias disciplinas, que incluyen desde las ciencias del comportamiento (análisis de decisiones, desagregación de preferencias), la inteligencia artificial (aprendizaje de preferencias), hasta la economía y el márqueting (teoría de la elección). Las tres corrientes, aunque originadas por diferentes filosofías, convergen rápidamente hacia una comprensión integral de las preferencias, que es el elemento básico para las decisiones y acciones humanas. Esta tesis doctoral profundiza en esta área de investigación mediante la introducción de un marco analítico integrado que permite capturar las preferencias de una forma compleja a partir de la observación de opciones holísticas, decisiones y juicios.
Preference disaggregation aims at capturing preference models by decomposing indirect preference information that are in form of holistic choices or judgments. From a multiple criteria decision aiding perspective, such information is taken as input to an inference procedure that yields to a preference model based on all the, usually conflicting, points of view that together form a basis for the judgments. Studying human judgments and choices has received increasing attention in the last few years from several disciplines, including behavioral science (decision analysis, preference disaggregation), artificial intelligence (preference learning), and economics and marketing (choice modeling). The three streams, although originated from different philosophies, are converging rapidly to a comprehensive understanding of human preferences, that is the main element of decisions and actions. This doctoral dissertation sheds light on this phenomenon by introducing an integrated analytical framework that allows capturing preferences of a complex form by observing holistic choices, decisions, and judgments.

Thesis (M.S. in Information Technology Management and M.S. in Computer Science)--Naval Postgraduate School, September 2002.
Thesis advisor(s): Alexander Bordetsky, Richard S. Coté. Michael P. Hadley received M.S. degrees in Information Technology Management and in Computer Science. James A. Wiest received a M.S. degree in Information Technology Management. Also available online.

Modeling comprehensive human decision behaviors in a unified and extensible framework is quite challenging. In this research, an integrated Belief-Desire-Intention (BDI) modeling framework is proposed to represent the human decision behavior, whose submodules (Belief, Desire, Decision-Making, and Emotion modules) are based on a Bayesian belief network (BBN), Decision-Field-Theory (DFT), a probabilistic depth first search (PDFS) technique, and a BBN-reinforcement (Q-Learning) hybrid learning algorithm. A key novelty of the proposed model is its ability to represent various human decision behaviors such as decision-making, decision-planning, and learning in a unified framework.To this end, first, we extend DFT (a widely known psychological model for preference evolution) to cope with dynamic environments. The extended DFT (EDFT) updates the subjective evaluation for the alternatives and the attention weights on the attributes via BBN under the dynamic environment. To illustrate and validate the proposed EDFT, a human-in-the-loop experiment is conducted for a virtual stock market. Second, a new approach to represent learning (a dynamic evolution process of underlying modules) in the human decision behavior is proposed under the context of the BDI framework. Our research focuses on how a human adjusts his perception process (involving BBN) dynamically against his performance (depicted via a confidence index) in predicting the environment as part of his decision-planning. To this end, Q-learning is employed and further developed.To mimic realistic human behaviors, attributes of the BDI framework are reverse-engineered from human-in-the-loop experiments conducted in the Cave Automatic Virtual Environment (CAVE). The proposed modeling framework is demonstrated for a human's evacuation behaviors in response to a terrorist bomb attack. The constructed simulation has been used to test the impact of several factors (e.g., demographics, number of police officers, information sharing via speakers) on evacuation performance (e.g., average evacuation time, percentage of casualties).In addition, the proposed human decision behavior model is extended for decisions of many stakeholders that form a complex social network in the community-based development of software systems.To the best of our knowledge, the proposed human decision behavior modeling framework is one of the first efforts to represent various human decision behaviors (e.g., decision-making, decision-planning, dynamic learning) in a unified BDI framework.

Interest in understanding Human Beings’ behaviour can be traced back to the early days of mankind. However, interest in consumer behaviour is relatively recent. In fact, it is only since the end of World War II and following economic prosperity of some nations (e.g., U.S.A.) that the world witnessed the rise of a new discipline in the early 1950s; namely, Marketing Research. By the end of the 1950s, academic papers on modelling and analysis of consumer behaviour started to appear (Ehrenberg, 1959; Frank, 1962). The purpose of this research is to propose an integrated decision framework for modelling consumer behaviour with respect to store incidence, category incidence, brand incidence, and size incidence. To the best of our knowledge, no published contribution integrates these decisions within the same modelling framework. In addition, the thesis proposes a new estimation method as well as a new segmentation method. These contributions aim at improving our understanding of consumer behaviour before and during consumers’ visits to the retail points of a distribution network, improving consumer behaviour prediction accuracy, and assisting with inventory management across distribution networks. The proposed modelling framework is hybrid in nature in that it uses both non-explanatory and explanatory models. To be more specific, it uses stochastic models; namely, probability distributions, to capture the intrinsic nature of consumers (i.e., inner or built-in behavioural features) as well as any unexplained similarities or differences (i.e., unobserved heterogeneity) in their intrinsic behaviour. In addition, the parameters of these probability distribution models could be estimated using explanatory models; namely, multiple regression models, such as logistic regression. Furthermore, the thesis proposes a piece-wise estimation procedure for estimating the parameters of the developed stochastic models. Also proposed is a three-step segmentation method based on the information provided by the quality of fit of stochastic models to consumer data so as to identify which model better predicts which market segments. In the empirical investigation, the proposed framework was used to study consumer behaviour with respect to individual alternatives of each decision, individual decisions, and all decisions. In addition, the proposed segmentation method was used to segment the panellists into infrequent users, light to medium users, and heavy users, on one hand, and split loyals, loyals, and hardcore loyals, on the other hand. Furthermore, the empirical evidence suggests that the proposed piece-wise estimation procedure outperforms the standard approach for all models and decision levels. Also, the empirical results revealed that the homogeneous MNL outperforms both the heterogeneous NMNL and DMNL when each one of these distributions is applied to all decisions, which suggests the relative homogeneity in consumer decision making at the aggregate or integrated decision level. Last, but not least, through the use of the proposed framework, the thesis sheds light on the importance of consumer choice sequence on the quality of predictions, which affects the quality of segmentation. The reader is referred to chapter 3 for details on these contributions.

Many environmental management tools have been developed aiming to reduce the impacts of dredging and protect the environment. As this has typically not been done in an integrated way that takes into account the socio-economic, environmental, technical and managerial aspects of dredging, there is a need to develop an integrated decision making tool to manage the impacts of dredging and help decision makers make sustainable decisions concerning dredging. The aim of this study was to develop a risk-based decision making framework for the integrated environmental management of dredging sediments in order to reduce the impacts of dredging and to lower the cost of environmental quality analysis and management. Selection of the best sediment management option using the risk-based approach of integrated environmental management has the potential to help effectively balance and prioritize the various socio-economic, environmental, technical and managerial aspects of dredging. The proposed framework will therefore utilize this concept throughout its six developmental steps. The first step reviews the literature on the impact of dredging and the two main factors that determine its magnitude, namely sediments and dredging technology. In order to manage the impacts of dredging efficiently, the relationship between scientific evidence and dredging activities will be assessed in the second developmental step. This step evaluates historical evidence from three dredging projects undertaken between 2006 and 2008 on the rivers of Sungai Sitiawan and Sungai Dinding, Perak, Malaysia. Monitoring and fish toxicological data from these projects are analyzed to determine their relationship with dredging activities performed in these rivers, with Geographic Information System (GIS) software used to illustrate the relationships found. The third developmental step assesses dredging problems other than the environmental impacts using Driving force-Pressure-State-Impact-Response (DPSIR) analysis, an IEM-based tool. This tool was employed in Malaysia’s dredging industry using interviews and a questionnaire-based survey. Dredging experts, including representatives from port operators, manufacturing companies and dredging contractors, were interviewed in 2008, with the socio-economy and management being found as the main drivers, together with environmental impacts, affecting dredging stakeholders in Malaysia. In 2010, further dredging experts (including marine ecologists, registered chemists, professional and chartered engineers, environmental consultants, university professors and environmental analysts) responded to the questionnaire, with results suggesting that governance of dredging in Malaysia is weak and that it is essential for Malaysia to review its current dredging environmental management tools and practices. The fourth developmental step develops the first stage (screening) of the proposed framework based on understanding provided by the three steps developed previously and demonstrated using Malaysia as a case study. This screening stage utilizes the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment (ERA) phases, which have been adjusted for benefits in cost, time and simplicity. Using case studies from Malaysia, the fifth developmental step (Tier 1) shows how Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria and is demonstrated for the Tier 1 stage. The results from MCDA will be integrated into Ecological Risk Assessment (ERA) to characterize the degree of contamination found in the areas. Priority areas, their degree of contamination and other concerns are then identified and brought forward to the sixth developmental step (Tier 2 stage). The Tier 2 stage is demonstrated using previous findings and analyzed using MCDA, in order to identify the best sediment management option, accounting for the economic, environmental and technical aspects of dredging.

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2005.
Amy R. Pritchett, Committee Member ; Moore, Mark D., Committee Member ; Wilhite, Alan, Committee Member ; Schrage, Daniel P., Committee Chair ; Mavris, Dimitri N., Committee Co-Chair ; DeLaurentis, Daniel A., Committee Member. Vita. Includes bibliographical references.

Risk assessment is an essential part of an effective transportation asset management program. The 2012 surface transportation bill, Moving Ahead for Progress in the 21st Century, requires state departments of transportation (DOTs) to establish risk- and performance-based asset management programs for the National Highway System. While the bill’s provisions include requirements only for pavement and bridge assets, they also recommend that DOTs consider other ancillary highway assets such as culverts and earth retaining structures, and hazards such as rockfalls and landslides. This research introduces an integrated risk framework with supporting algorithms to provide for the integration of ancillary assets and hazards into existing transportation asset management systems, and facilitate budget planning and resource allocation. The framework, Highway Assets Risk Management Decision-Support System (HARM-DSS), adopts a system-of systems perspective in defining and evaluating performance, and analyzing and addressing risk. The algorithms are developed using multi-criteria decision analysis (MCDA) and risk analysis methods; value functions are applied to scale performance attributes, and additive weighting to integrate multiple risk criteria. The methodology is applied at the corridor-level to analyze three different case studies using data with notable variability from New York, Minnesota and Oregon. The cases demonstrate the process for developing descriptive and visual information on multi-asset/hazard corridors, with sparse to medium data, in order to identify corridors that are vulnerable to failure, as well as exhibit high risk of failure within a transportation network. The results demonstrate that HARM-DSS can be applied across competing corridors or alternatives to produce descriptive and intuitive results that decision makers can use in budget planning and resource allocation. This research extends the risk-based thinking on transportation asset management, by moving it from a silo-ed to an integrated analytical platform that considers multiple non-homogenous assets and hazards simultaneously. It identifies data deficiencies and offers recommendations on the requisite data collection on asset inventory and condition to improve objectivity in the analytical process and confidence in the analysis results. In addition, it offers recommendations on the appropriate use of expert knowledge in supplementing existing data deficiencies in the interim. This work is potentially useful to decision makers involved in distributing resources to preserve the reliability and resiliency of transportation systems, as well as meet the existing performance- and risk-based Federal mandates for transportation asset management.

Thesis (Ph. D.)--Mechanical Engineering, Georgia Institute of Technology, 2006.
Eastman, Chuck, Committee Member ; Paredis, Chris, Committee Co-Chair ; Allen, Janet, Committee Member ; Rosen, David, Committee Member ; Tsui, Kwok, Committee Member ; McDowell, David, Committee Member ; Mistree, Farrokh, Committee Chair. Includes bibliographical references.

In the UK, the debate surrounding energy production lies at the forefront of the political agenda, with growing emphasis on achieving an increasingly sustainable energy mix into the future. The nuclear option is especially debatable - issues such as waste management and decommissioning receive much attention. In addition, the many stakeholders interested in nuclear power display very divergent views on its sustainability. Since the turn of the century, nuclear power has received much attention globally, with many nations’ governments taking consideration of the potential benefits of new nuclear adoption. Conversely, the Fukushima nuclear disaster has led to new nuclear resistance in other nations, such as Germany, where plans have been made to stop nuclear power generation completely. This research aims to help inform the debate on nuclear power and the future UK electricity mix. A multi-criteria decision support framework (developed by the SPRIng Project) has been used for these purposes, taking into account technical, economic, environmental and social criteria.The methodology used in this work has involved: stakeholder consultation; use of future electricity scenarios; sustainability assessment of current and future electricity options (Pressurised Water Reactor, European Pressurised Reactor, European Fast Rector, coal, gas, solar and wind power, and coal carbon capture and storage [CCS] power); assessment of future electricity scenarios based on both sustainability impacts and stakeholder (expert and public) preferences for the sustainability indicators and electricity technologies. The sustainability assessment of future nuclear power options and coal CCS power have been carried out here for the first time in a UK-specific context.Based on the public and expert opinions on the importance of different sustainability indicators, results of the scenario analysis suggest that the scenario with a high penetration of low-carbon technologies (nuclear [60%] and offshore wind power [40%]) is the most sustainable. For the sample considered in this study, this finding is not sensitive to different stakeholder and public opinions on the importance of the sustainability indicators. However, when the stakeholder preferences for individual technologies are considered, scenarios with high penetration of renewables (26-40% solar and 20-48% wind) become the preferred options. This is due to the favourable stakeholder opinion on solar and wind power. In that case, the scenario with high penetration of nuclear is never the preferred option due to the low to moderate stakeholder preference for nuclear power.Therefore, the results from this research suggest that the ‘sustainability’ of different electricity options and scenarios is highly dependent on stakeholder preferences and priorities. Thus, for successful future deployment of these options and implementation of energy policy measures, transparency of information on the impacts of electricity options is key in ensuring that stakeholder opinions are founded in the actual rather than the perceived impacts of these options.

The current application of logistics in the construction industry is relatively inefficient when compared with other industries such as retail and manufacturing. The factors attributed to this inefficiency include the fragmented and short-term nature of construction process and inadequate tracking facilities on site. The inefficiency of construction logistics creates inter alia loss of materials and equipment, waste, construction delay, excessive cost and collision accident on site. Meanwhile, several information and communication technologies (ICT) have been proposed and developed by researchers to improve logistics functions such as tracking and monitoring of resources through the supply chain to the construction site. Such technologies include global positioning system (GPS), radio frequency identification devices (RFID), wireless sensors network (WSN) and geographical information system (GIS). While considerable research has been undertaken to develop the aforementioned systems, limited work has so far been done on investment justification prior to implementation. In this research, a framework has been developed to assess the extent of construction logistics problems, measure the significances of the problems, match the problems with existing ICT-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several ICT-based construction logistics systems. The tool is an integrated platform of related evaluation techniques such as Fault Tree Analysis, Decision Tree Analysis, Life Cycle Cost Analysis and Multi-Attribute Utility Theory. Prior to the development of this tool, data was collected through questionnaire survey and analysed by means of statistical analysis in order to derive some foundational parameters of the tool. Quantitative research method was adopted for data collection because the processes of the tool for which the data was required are quantitative. The implementation of this tool is novel given the integration of the analytical techniques mentioned above and the application of the tool for selecting ICT-based construction logistics systems. The tool takes in data such as cost and quantities of materials for a building project and quantifies the cost and benefits of alternative ICT-based tracking systems that can improve the logistics functions of the project. The application of the tool will eliminate guesswork on the benefits of ICT-based tracking systems by providing an objective platform for the quantification of cost and benefits of the systems prior to implementation.

This research proposes a risk management framework and develops generic risk-based decision-making, and risk-assessment models for dealing with potential Hazard Events (HEs) and risks associated with uncertainty for Operational Safety Performance (OSP) in container terminals and maritime ports. Three main sections are formulated in this study: Section 1: Risk Assessment, in the first phase, all HEs are identified through a literature review and human knowledge base and expertise. In the second phase, a Fuzzy Rule Base (FRB) is developed using the proportion method to assess the most significant HEs identified. The FRB leads to the development of a generic risk-based model incorporating the FRB and a Bayesian Network (BN) into a Fuzzy Rule Base Bayesian Network (FRBN) method using Hugin software to evaluate each HE individually and prioritise their specific risk estimations locally. The third phase demonstrated the FRBN method with a case study. The fourth phase concludes this section with a developed generic risk-based model incorporating FRBN and Evidential Reasoning to form an FRBER method using the Intelligence Decision System (IDS) software to evaluate all HEs aggregated collectively for their Risk Influence (RI) globally with a case study demonstration. In addition, a new sensitivity analysis method is developed to rank the HEs based on their True Risk Influence (TRI) considering their specific risk estimations locally and their RI globally. Section 2: Risk Models Simulations, the first phase explains the construction of the simulation model Bayesian Network Artificial Neural Networks (BNANNs), which is formed by applying Artificial Neural Networks (ANNs). In the second phase, the simulation model Evidential Reasoning Artificial Neural Networks (ERANNs) is constructed. The final phase in this section integrates the BNANNs and ERANNs that can predict the risk magnitude for HEs and provide a panoramic view on the risk inference in both perspectives, locally and globally. Section 3: Risk Control Options is the last link that finalises the risk management based methodology cycle in this study. The Analytical Hierarchal Process (AHP) method was used for determining the relative weights of all criteria identified in the first phase. The last phase develops a risk control options method by incorporating Fuzzy Logic (FL) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to form an FTOPSIS method. The novelty of this research provides an effective risk management framework for OSP in container terminals and maritime ports. In addition, it provides an efficient safety prediction tool that can ease all the processes in the methods and techniques used with the risk management framework by applying the ANN concept to simulate the risk models.

Designing Net-Zero Energy Buildings (NZEB) is a complex and collaborative team process involving knowledge sharing of experts leading to the common goal of meeting the Net-Zero Energy (NZE) project objectives. The decisions made in the early stages of design drastically affect the final outcome of design and energy goals. The Architecture, Engineering and Construction (AEC) industry is pursuing ways to improve the current building design process and project delivery methods for NZEBs. To enable the building industry to improve the building design process, it is important to identify the gaps, ways of improvement and potential opportunities to structure the decision-making process for the purpose of NZE performance outcome. It is essential to identify the iterative phases of design decisions between the integrated team of experts for the design processes conducted in these early stages to facilitate the decision-making of NZEB design. The lack of a structured approach to help the AEC industry in making informed decisions for the NZEB context establishes the need to evaluate the argumentation of the NZEB design decision process. The first step in understanding the NZEB design decision process is to map the current processes in practice that have been successful in achieving the NZE goal. Since the energy use performance goal drives the design process, this research emphasizes first the need to document, in detail, and investigate the current NZEB design process with knowledge mapping techniques to develop an improved process specific to NZEB context. In order to meet this first objective, this research qualitatively analyzed four NZEB case studies that informed decision-making in the early design phases. The four components that were studied in the early design phases included (1) key stakeholders involved (roles played), (2) phases of assessments (design approach, (3) processes (key processes, sub-processes and design activities affecting performance) and (4) technology (knowledge type and flow). A series of semi-structured, open-ended interviews were conducted with the key decision-makers and decision facilitators to identify their roles in the early design processes, the design approach adopted, rationale for decision-making, types of evaluations performed, and tools used for analysis. The qualitative data analysis was performed through content analysis and cognitive mapping techniques. Through this process, the key phases of decision-making were identified that resulted in understanding of the path to achieving NZE design goal and performance outcome. The second objective of this research was to identify the NZE decision nodes through a comparative investigation of the case studies. This research also explored the key issues specific to each stakeholder group. The inter-relationships between the project objectives, decision context, occupants usage patterns, strategies and integrated systems, building operation and renewable energy production was identified through a series of knowledge maps and visual process models leading to the identification of the key performance indicators. This research reviewed the similarities and differences in the processes to identify significant opportunities that can improve the early building design process for NZEBs. This research identifies the key decision phases used by the integrated teams and describes the underlying structure that can change the order of key phases. A process mapping technique was adapted to capture the practice-based complex NZEB design approach and draw insights of the teamwork and interdisciplinary communication to enable more comprehensive understanding of linkages between processes, sub-processes and design activities, knowledge exchange, and decision rationale. Ket performance indicators identified for early design of NZEBs resulted in developing a decision-support process model that can help the AEC industry in making informed decisions. This dissertation helps improve understanding of linkages between processes, decision nodes and decision rationale to enable industry-wide NZEB design process assessment and improvement. This dissertation discusses the benefits the proposed NZEB design process model brings to the AEC industry and explores future development efforts.
Ph. D.

This work focuses on the need for new knowledge to allow hierarchical multi-project management to be conducted in the construction industry, which is characterised by high uncertainty, fragmentation, complex decisions, dynamic changes and long-distance communication. A dynamic integrated project management approach is required at strategic, tactical and operational levels in order to achieve adaptability. The work sees the multi-project planning and control problem in the context of supply chain management at main contractor companies. A portfolio manager must select and prioritise the projects, bid and negotiate with a wide range of clients, while project managers are dealing with subcontractors, suppliers, etc whose relationships and collaborations are critical to the optimisation of schedules in which time, cost and safety (etc) criteria must be achieved. Literature review and case studies were used to investigate existing approaches to hierarchical multi-project management, to identify the relationships and interactions between the parties concerned, and to investigate the possibilities for integration. A system framework was developed using a multi-agent-system architecture and utilising procedures adapted from literature to deal with short, medium and long-term planning. The framework is based on in-depth case study and integrates time-cost trade-off for project optimisation with multi-attribute utility theory to facilitate project scheduling, subcontractor selection and bid negotiation at the single project level. In addition, at the enterprise level, key performance indicator rule models are devised to align enterprise supply chain configuration (strategic decision) with bid selection and bid preparation/negotiation (tactical decision) and project supply chain selection (operational decision). Across the hierarchical framework the required quantitative and qualitative methods are integrated for project scheduling, risk assessment and subcontractor evaluation. Thus, experience sharing and knowledge management facilitate project planning across the scattered construction sites. The mathematical aspects were verified using real data from in-depth case study and a test case. The correctness, usefulness and applicability of the framework for users was assessed by creating a prototype Multi Agent System-Decision Support System (MAS-DSS) which was evaluated empirically with four case studies in national, international, large and small companies. The positive feedback from these cases indicates strong acceptance of the framework by experienced practitioners. It provides an original contribution to the literature on planning and supply chain management by integrating a practical solution for the dynamic and uncertain complex multi-project environment of the construction industry.

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 154-158).
Companies today must constantly innovate to delight consumers and stay ahead of the competition. One way to deliver these is through new product launches. Despite significant investments, product failure rate in consumer products industry is high. Studies attribute failures to lack of quality and lack of integration of consumer insight in the Product Development Process. This thesis is an attempt for improvement, adopting the lens of consumer insight as information in the Product Development Process, and proposes a method to evaluate options more strategically. This thesis first examines available literature on Product Development Processes and consumer insight methodologies. It then uses Design Structure Matrix to identify consumer insight involvement in Product Development Process, and identifies gaps between the theoretical model and industry practice. Thereafter, this thesis proposes a technique to compare the quality of different consumer research methods at a given point in the process. Using this information, this thesis builds a Quantitative model to simulate the propagation effect of individual consumer insights decision on quality of output information, using rate of market change as a secondary factor. Within the constraints of this model, it was found that consumer insight strategy decisions should not be done in an ad-hoc manner, since consumer research method selection at each point in the Product Development Process has direct and propagative effects on the quality of the outcome. To obtain good quality, the selection of a good method is critical; first, because it allows for flexibility of options in subsequent phases, and second, because it is more effective than rework, under Slow and Rapid rate of market change. This thesis proposes decision and implementation frameworks as a guide for Product Managers, who can combine the predicted outcome of consumer insight quality with project management iron triangle, to select the best consumer insight strategy. While this consumer insight systemic model is a step towards a model-based design of consumer insight strategy, future work is needed to validate the quantitative model and resulting decision framework.
by Lenni Kimawati.
S.M. in Engineering and Management

In order to stay competitive in today’s overly competitive market place, businesses must be engineered to match product characteristics and customer requirements. This increased emphasis on achieving highly adaptive manufacturing with reduction in manufacturing costs, better utilization of manufacturing resources and sound environmental management practices force organisations to adopt efficient management practices in their manufacturing operations. Some of the established practices in this context belong to the Lean, Agility and Green (LAG) paradigms. Adopting these practices in order to address customer requirements may require some level of expertise and understanding of the contribution (or lack of it) of the practices in meeting those requirements. Primarily, the wide choice of LAG practices available to address customer requirements can be confusing and/or challenging for those with limited knowledge of LAG practices and their efficacy. There is currently no systematic methodology available for selecting appropriate LAG practices considering of the product life cycle (PLC). Therefore, this research provides a novel framework for selecting appropriate LAG practices based on PLC stages for reducing costs, lead time and generated waste. The methodology describes the application of analytic hierarchy process (AHP), statistical inference and regression analysis as decision support tools, ensuring a systematic approach to the analysis with appropriate performance measures. The data collected were analysed with the aid of SPSS and Excel using a variety of statistical methods. The framework was verified through a Delphi study and validated using a case study. The key findings of the research include the various contributions of lean, agile and green practices towards improving performance measures, the importance of green in improving performance measures and the importance of selecting appropriate practices based on product life cycle stages. This research makes a clear contribution to existing body of knowledge by providing a methodological framework which could serve as a guide for companies in the FMCG industry to systematically integrate and adopt lean, agile and green to better manage their processes and meet customer requirements in their organisations. However, the framework developed in this research has not been tested in other areas.

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

A modeling framework to evaluate the costs and benefits of implementation of Con-troller Pilot Data Link Communication (CPDLC), and Air Traffic Management (ATM) decision support tools is proposed in this paper. The benefit/cost evaluation is carried out for four key alternatives namely alternative A: Do nothing scenario (only voice channel), alternative B: Voice channel supplemented with CPDLC, alternative C: Alternative B with ATM tools in a non-integrated scenario and finally alternative D: Alternative B with ATM tools in an integrated scenario. It is a bi-level model that cap-tures the linkages between various technologies at a lower microscopic level using a daily microscopic model (DATSIM) and transfers the measures of effectives to a higher macroscopic level. DATSIM stands for Data Link and Air Traffic Technologies SIMulation and it simulates air traffic in the enroute sector and terminal airspace for a single day and captures the measures of effectiveness at a microscopic level and feeds its output to the macroscopic annual model which then runs over the entire life cycle of the system. Airspace dwell time benefit data from the microscopic model is regressed into three dimensional benefit surfaces as a function of the equipage level of aircraft and aircraft density and embedded into the macroscopic model. The main function of the annual model is to ascertain economic viability of any deployment schedule or alternative over the entire life cycle of the system. The life cycle cost model is com-posed of four modules namely: Operational benefits module, Safety benefit module,Technology cost module and Training cost module. Analysis using the model showed that an enroute sector gets congested at aircraft den-sities greater 630 per day. This is mainly because the controller workload gets satu-rated at that traffic volume per day. Benefits realized in alternatives B, C and D as compared to alternative A increased exponentially at traffic densities greater than 630 i.e. when controller workload for alternative A becomes saturated.
Master of Science

On the way towards a more biobased economy, the sustainable use of global wood resources remains a challenge as several trade-offs arise, e.g., from an increased energetic use of wood, an increased use of innovative but probably less recyclable wood composites, or from the need to conserve other forest ecosystem services. The aim of this study is to identify existing environmental indicators and methods for an evaluation of the sustainability of wood products in consideration of all life cycle stages, site-dependent aspects and later use in corporate decision-making. We chose a systematic literature review to answer the research questions explicitly and comprehensively. Qualitative content analysis was used to code indicators and scientific methods according to the Pressure-State-Response (PSR) framework. The sample (N = 118) is characterized by a high number of life cycle assessment (LCA) case studies. In 51% of all studies, the study authors use a combination of different methods. A total of 78 indicators and 20 site-dependent aspects could be identified in the sample. The study findings represent a first step towards a holistic environmental assessment of wood products.

Management of water bodies according to their river basinsis becoming increasingly common, as the concept of IntegratedWater Resources Management (IWRM) is getting more and moreacknowl-edged. In Europe, a large portion of these“new”management units will probably be internationalor transboundary. Decisions and policies consideringtransboundary water issues need to be based on reliable andcomprehendible information. In this thesis, a review of variousexisting models that may be used for understanding the role anduse of information in (transboundary) water management ispresented. Further, the thesis reports on an assessment of theinformation management of three transboundary water regimes inEurope, namely the international water commissions for LakeNeusiedl, Lake Constance and Elbe River. Besides examining theinformation management of the regimes as such, the managementwas also related to information needs implied by the IWRMcon-cept and by the EU Water Framework Directive (WFD). Thereviewed models and approaches were grouped into threecategories: information management models, information cyclemodels and communication between actors. The first categorycomprised models that may be used for managing and assessingdifferent types of information. The second group dealt withmodels explaining the production and communication ofinformation predominately from an information producer/senderperspective. The third group focused on ideas concerninginteractions and communication of information between differentkinds of actors. The studies on information management intransboundary water regimes showed that the information needsand strategies often were defined primarily with watercommissions’own needs in mind. The data collected by thecommissions were predominated by monitoring data, describingthe status of the environment and the impact caused by humanactivities. Furthermore, any communication of information toother groups of actors was mainly done through passivechannels. The information management in these transboundarywater regimes was not fully in accordance with informationneeds implied by the IWRM concept and the EU WFD.

Keywords:Integrated Water Resources Management (IWRM);transboundary water management; information; EU Water FrameworkDirective (WFD); regimes; policy and decision making; LakeNeusiedl; Lake Constance; Elbe River.

Most large cities around the world are undergoing rapid transport sector development to cater for increased urbanization. Subsequently the issues of mobility, access equity, congestion, operational safety and above all environmental sustainability are becoming increasingly crucial in transport planning and policy making. The popular response in addressing these issues has been demand management, through improvement of motorised public transport (MPT) modes (bus, train, tram) and non-motorized transport (NMT) modes (walk, bicycle); improved fuel technology. Relatively little attention has however been given to another readily available and highly sustainable component of the urban transport system, non-motorized public transport (NMPT) such as the pedicab that operates on a commercial basis and serves as an NMT taxi; and has long standing history in many Asian cities; relatively stable in existence in Latin America; and reemerging and expanding in Europe, North America and Australia. Consensus at policy level on the apparent benefits, costs and management approach for NMPT integration has often been a major transport planning problem. Within this context, this research attempts to provide a more complete analysis of the current existence rationale and possible future, or otherwise, of NMPT as a regular public transport system. The analytical process is divided into three major stages. Stage 1 reviews the status and role condition of NMPT as regular public transport on a global scale- in developing cities and developed cities. The review establishes the strong ongoing and future potential role of NMPT in major developing cities. Stage 2 narrows down the status review to a case study city of a developing country in order to facilitate deeper role review and status analysis of the mode. Dhaka, capital city of Bangladesh, has been chosen due to its magnitude of NMPT presence. The review and analysis reveals the multisectoral and dominant role of NMPT in catering for the travel need of Dhaka transport users. The review also indicates ad-hoc, disintegrated policy planning in management of NMPT and the need for a planning framework to facilitate balanced integration between NMPT and MT in future. Stage 3 develops an integrated, multimodal planning framework (IMPF), based on a four-step planning process. This includes defining the purpose and scope of the planning exercise, determining current deficiencies and preferred characteristics for the proposed IMPF, selection of suitable techniques to address the deficiencies and needs of the transport network while laying out the IMPF and finally, development of a delivery plan for the IMPF based on a selected layout technique and integration approach. The output of the exercise is a planning instrument (decision tool) that can be used to assign a road hierarchy in order to allocate appropriate traffic to appropriate network type, particularly to facilitate the operational balance between MT and NMT. The instrument is based on a partial restriction approach of motorised transport (MT) and NMT, structured on the notion of functional hierarchy approach, and distributes/prioritises MT and NMT such that functional needs of the network category is best complemented. The planning instrument based on these processes and principles offers a six-level road hierarchy with a different composition of network-governing attributes and modal priority, for the current Dhaka transport network, in order to facilitate efficient integration of NMT with MT. A case study application of the instrument on a small transport network of Dhaka also demonstrates the utility, flexibility and adoptability of the instrument in logically allocating corridors with particular positions in the road hierarchy paradigm. Although the tool is useful in enabling balanced distribution of NMPT with MT at different network levels, further investigation is required with reference to detailed modal variations, scales and locations of a network to further generalise the framework application.

Les pénuries d'électricité sont un problème mondial majeur à cause de l'augmentation de la demande d'électricité, c'est pourquoi l’implémentation des énergies renouvelables(ER) est une solution alternative importante pour répondre à nos besoins en électricité, en réduisant les émissions de gaz à effet de serre pour lutter contre le changement climatique et d'atténuer la dépendance à l'égard des ressources en combustibles fossiles. Ainsi, la planification de la transition vers les ER est une stratégie essentielle que le réseau électrique soit connecté au nationale ou hors dans les zones rurales. La plupart des pays sont déjà commencé à renforcer leurs infrastructures énergétiques pour les alimenter à partir de ressources ER durables, mais les ressources potentielles limitées pourraient arrêter ce déploiement. L’intégration de différentes ressources d'ER au réseau électrique est un enjeu majeur pour assurer la stabilité et l’implémentation de systèmes d'ER à rendement nécessite à la prise de décision pour encourager d'investissement. Donc, la planification des ER doit être évaluée à partir des critères technico-économiques et socio-environnementaux. Cette thèse surligner le concept principal de la transition 100 % ER d’ici fin 2030 en Guyane française où il y a un enjeu dans l'élaboration du scénario énergétique d'ici 2030 et les centrales électriques actuelles ne peuvent pas se nourrir l'augmentation de la demande d'électricité avec des ressources limitées. En résumé, cette thèse répondra à la question : comment optimiser différents scénarios de production d'énergie en tenant compte des dimensions spatio-temporelles du problème et des données
Currently, lack of electricity is a major global issue around the world due to the increase in power demand, that’s why implementation of renewable energy(RE) is an important alternative solution to feed our electricity needs, reducing Green House Gases (GHG) emissions to fight climate change and to mitigate the dependency on fossil fuels resources. So, (RE) transition planning is an essential ongoing strategy to feed our demand needs whether the network is grid-connected or off-grid in rural areas. Most countries have already begun to reinforce its energy infrastructure to be fed from sustainable (RE) resources but the limited potential resources could halt such deployment. So, integration of different renewable energy resources to the power network is a major challenge to secure the stability of the grid and the implementation of efficient (RE) systems requires strong decision making support to encourage investments. Thus, (RE) planning should be evaluated from the techno-economic-socio-environmental criteria. This thesis highlights the main concept of 100 % renewable energy transition by the end of 2030 in French Guiana where there is a challenge in the development of the energetic scenario by 2030 and the current energy production facilities cannot feed the increase in power demand within limited resources. As a summary, this thesis handles this research question: how to optimize different energy production scenarios combining different RE resources of maximum production at minimal costs in order to satisfy the energy needs taking into account the spatio-temporal dimensions of the problem and data?

The application of environmental performance indicators (EPIs) has received increasing attention by both governments and international organisations as a tool for assessing complex environmental scenarios in national and local decision making processes. However, at the regional scale there is a gap in the application of EPIs, as this has not been well understood and defined due to a limited theoretical foundation and often insufficient data from all participant countries. The regional scale is important because it can incorporate natural ecosystems which often transcend national boundaries. A case study is developed for the Lower Mekong Subregion (LMS), where four riparian Southeast Asian countries (Lao PDR, Thailand, Cambodia, and Viet Nam) share the Lower Mekong River. The research proposes a conceptual framework to identify approaches for developing criteria for acceptable and appropriate EPIs which can be used to support and implement decision making processes by relevant organisations at the regional level. This research evaluates the application of environmental performance indicators using methodologies that assess cross-national quantitative and qualitative data and existing decision support systems. In addition, global and national indicators are examined for application and relation to the regional context. The research finds that the application of EPIs varies according to spatial scale, and is diverse among the four countries. Data availability is also identified as a major problem encountered during the development and selection of EPIs. The study finds that the governance of the existing regional body is ineffective due to differing agendas pursued by each participating country. This is because the current regional body is structured only to facilitate information exchange and cooperation in a limited manner, focusing so far only on water management issues. LMS regional goals need to be set in order to guide the stakeholders in identifying an appropriate set of EPIs. Most importantly, the research is intended to be a catalyst for encouraging the participants to integrate methods and other species of EPIs proposed in this research in their environmental assessment policies.

The application of environmental performance indicators (EPIs) has received increasing attention by both governments and international organisations as a tool for assessing complex environmental scenarios in national and local decision making processes. However, at the regional scale there is a gap in the application of EPIs, as this has not been well understood and defined due to a limited theoretical foundation and often insufficient data from all participant countries. The regional scale is important because it can incorporate natural ecosystems which often transcend national boundaries. A case study is developed for the Lower Mekong Subregion (LMS), where four riparian Southeast Asian countries (Lao PDR, Thailand, Cambodia, and Viet Nam) share the Lower Mekong River. The research proposes a conceptual framework to identify approaches for developing criteria for acceptable and appropriate EPIs which can be used to support and implement decision making processes by relevant organisations at the regional level. This research evaluates the application of environmental performance indicators using methodologies that assess cross-national quantitative and qualitative data and existing decision support systems. In addition, global and national indicators are examined for application and relation to the regional context. The research finds that the application of EPIs varies according to spatial scale, and is diverse among the four countries. Data availability is also identified as a major problem encountered during the development and selection of EPIs. The study finds that the governance of the existing regional body is ineffective due to differing agendas pursued by each participating country. This is because the current regional body is structured only to facilitate information exchange and cooperation in a limited manner, focusing so far only on water management issues. LMS regional goals need to be set in order to guide the stakeholders in identifying an appropriate set of EPIs. Most importantly, the research is intended to be a catalyst for encouraging the participants to integrate methods and other species of EPIs proposed in this research in their environmental assessment policies.

Energy forms a vital input and critical infrastructure for the economic development of countries and for improving the quality of life of people. Energy is utilized in society through the operation of large socio-technical systems called energy systems. In a growing world, as the focus shifts to better access and use of modern energy sources, there is a rising demand for energy. However, certain externalities result in this demand not being met adequately, especially in developing countries. This constitutes the energy demand – supply matching problem. Load shedding is a response used by distribution utilities in developing countries, to deal with the energy demand – supply problem in the short term and to secure the grid. This response impacts the activities of consumers and entails economic losses. Given this scenario, demand – supply matching becomes a crucial decision making activity. Traditionally demand – supply matching has been carried out by increasing supply centrally in the long term or reducing demand centrally in the short term. Literature shows that these options have not been very effective in solving the demand-supply problem. Gaps in literature also show that the need of the hour is the design of alternate solutions which are tailored to a nation's specific energy service needs in a sustainable way. Microgrids using renewable and clean energy resources and demand side management can be suitable decentralized alternatives to augment the centralized grid based systems and enable demand – supply matching at a local community level. The central research question posed by this thesis is: “How can we reduce the demand – supply gap existing in a community, due to grid insufficiency, using locally available resources and the grid in an optimal way; and thereby facilitate microgrid implementation?” The overall aim of this dissertation is to solve the energy demand – supply matching problem at the community level. It is known that decisions for the creation of energy systems are influenced by several factors. This study focuses on those factors which policy-makers and stakeholders can influence. It proposes an integrated decision framework for the creation of community microgrids. The study looks at several different dimensions of the existing demand – supply problem in a holistic way. The research objectives of this study are: 1. To develop an integrated decision framework that solves the demand – supply matching problem at a community level. 2. To decompose the consumption patterns of the community into end-uses. solar thermal, solar lighting and solar pumps and a combination of these at different capacities. The options feasible for medium income consumers are solar thermal, solar pumps, municipal waste based systems and a combination of these. The options for high income consumers are municipal waste based CHP systems, solar thermal and solar pumps. Residential consumers living in multi-storied buildings also have the options of CHP, micro wind and solar. For cooking, LPG is the single most effective alternative. 3. To identify the ‗best fitting‘ distributed energy system (microgrid), based on the end-use consumption patterns of the community and locally available clean and renewable energy resources, for matching demand – supply at the community level. 4. To facilitate the implementation of microgrids by * Contextualizing the demand – supply matching problem to consider the local social and political environment or landscape, * Studying the economic impact of load shedding and incorporating it into the demand-supply matching problem, and * Presenting multiple decision scenarios, addressing the needs of different stakeholders, to enable dialogue and participative decision making. A multi-stage Integrated Decision Framework (IDF) is developed to solve the demand - supply matching problem in a sequential manner. The first stage in the IDF towards solving the problem is the identification and estimation of the energy needs / end-uses of consumers in a community. This process is called End-use Demand Decomposition (EUDD) and is accomplished by an empirical estimation of consumer electricity demand based on structural and socio-economic factors. An algorithm/ heuristic is also presented to decompose this demand into its constituent end-uses at the community level for the purpose of identifying suitable and optimal alternatives/ augments to grid based electricity. The second stage in the framework is Best Fit DES. This stage involves identifying the “best-fit‘ distributed energy system (microgrid) for the community that optimally matches the energy demand with available forms of supply and provides a schedule for the operation of these various supply options to maximize stakeholder utility. It provides the decision makers with a methodology for identifying the optimal distributed energy resource (DER) mix, capacity and annual operational schedule that “best fits” the given end-use demand profile of consumers in a community and under the constraints of that community such that it meets the needs of the stakeholders. The optimization technique developed is a Mixed Integer Linear Program and is a modification of the DER-CAM™ (Distributed Energy Resources Customer Adoption Model), which is developed by the Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory using the GAMS platform. The third stage is the Community Microgrid Implementation (CMI) stage. The CMI stage of IDF includes three steps. The first one is to contextualize the energy demand and supply for a specific region and the communities within it. This is done by the Energy Landscape Analysis (ELA). The energy landscape analysis attempts to understand the current scenario and develop a baseline for the study. It identifies the potential solutions for the demand - supply problem from a stakeholder perspective. The next step provides a rationale for the creation of community level decentralized energy systems and microgrids from a sustainability perspective. This is done by presenting a theoretical model for outage costs (or load shedding), empirically substantiating it and providing a simulation model to demonstrate the viability for distributed energy systems. Outage cost or the cost of non supply is a variable that can be used to determine the need for alternate systems in the absence/ unavailability of the grid. The final step in the CMI stage is to provide a scenario analysis for the implementation of community microgrids. The scenario analysis step in the framework enlightens decision makers about the baselines and thresholds for the solutions obtained in the “best fit‘ analysis. The first two stages of IDF, EUDD and Best Fit DES, address the problem from a bottom-up perspective. The solution obtained from these stages constitutes the optimal solution from a technical perspective. The third stage CMI is a top-down approach to the problem, which assesses the social and policy parameters. This stage provides a set of satisficing solutions/ scenarios to enable a dialogue between stakeholders to facilitate implementation of microgrids. Thus, IDF follows a hybrid approach to problem solving. The proposed IDF is then used to demonstrate the choice of microgrids for residential communities. In particular, the framework is demonstrated for a typical residential community, Vijayanagar, situated in Bangalore and the findings presented. The End-use Demand Decomposition (EUDD) stage provides the decision makers with a methodology for estimating consumer demand given their socio-economic status, fuel choice and appliance profiles. This is done by the means of a statistical analysis. For this a primary survey of 375 residential households belonging to the LT2a category of BESCOM (Bangalore Electricity Supply Company) was conducted in the Bangalore metropolitan area. The results of the current study show that consumer demand is a function of the variables family income, refrigeration, entertainment, water heating, family size, space cooling, gas use, wood use, kerosene use and space heating. The final regression model (with these variables) can effectively predict up to 60% of the variation in the electricity consumption of a household ln(ElecConsumption) = 0.2880.396*ln(Income)+0.2 66*Refri geration+ 0.708*Entertainment+0.334*WaterHeating+0.047*FamSize+ 0243*SpaceCooling.+580*GasUse+0.421*WoodUse–0.159*KeroseneUse+ 0.568*SpaceHeating ln(ElecConsumption) = 0.406*ln(Income)0.168*Ref rigeration+0.139*Entertainment+ 0.213*WaterHeating+0.114*FamSize+0.121*SpacCooling+0.171*GasUse+ 0.115*WoodUse–0.094*KeroseneUse+0.075*SpaceHeating   The next step of EUDD is to break up the demand into its constituent end-uses. The third step involves aggregating the end-uses at the community level. These two steps are to be performed using a heuristic. The Best Fit DES stage of IDF is demonstrated with data from an urban community in Bangalore. This community is located in an area called Vijayanagar in Bangalore city. Vijayanagar is a mainly a residential area with some pockets of mixed use. Since grid availability is the constraining parameter that yields varying energy availability, this constraint is taken as the criteria for evaluation of the model. The Best Fit DES model is run for different values of the grid availability parameter to study the changes in outputs obtained in DER mix, schedules and overall cost of the system and the results are tabulated. Sensitivity analysis is also performed to study the effect of changing load, price options, fuel costs and technology parameters. The results obtained from the BEST Fit DES model for Vijayanagar illustrate that microgrids and DERs can be a suitable alternative for meeting the demand – supply gap locally. The cost of implementing DERs is the optimal solution. The savings obtained from this option however is less than 1% than the base case due to the subsidized price of grid based electricity. The corresponding costs for different hours of grid availability are higher than the base case, but this is offset by the increased efficiency of the overall system and improved reliability that is obtained in the community due to availability of power 24/7 regardless of the availability of grid based power. If the price of grid power is changed to reflect the true price of electricity, it is shown that DERs continue to be the optimal solution. Also the combination of DERs chosen change with the different levels of non-supply from the grid. For the study community, Vijayanagar, Bangalore, the DERs chosen on the basis of resource availability are mainly discrete DERs. The DERs chosen are the LPG based CHP systems which run as base and intermediate generating systems. The capacity of the discrete DERs selected, depend on the end-use load of the community. Biomass based CHP systems are not chosen by the model as this technology has not reached maturity in an urban setup. Wind and hydro based systems are not selected as these resources are not available in Vijayanagar. The CMI stage of IDF demonstrates the top-down approach to the demand-supply matching problem. For the Energy Landscape Analysis (ELA), Bangalore metropolis was chosen in the study for the purpose of demonstration of the IDF framework. Bangalore consumes 25% of the state electricity supply and its per capita consumption at 1560kWh is higher than the state average of 1230kWh and is 250% more than the Indian average of 612kWh. A stakeholder workshop was conducted to ascertain the business value for clean and renewable energy technologies. From the workshop it was established that significant peak power savings could be obtained with even low penetrations of distributed energy technologies in Bangalore. The feasible options chosen by stakeholders for low income consumers are The second step of CMI is finding an economic rationale for the implementation of community microgrids. It is hypothesized that the ‘The cost of non-supply follows an s-shaped curve similar to a growth curve.’ It is moderated by the consumer income, consumer utility, and time duration of the load shedding. A pre and post event primary survey was conducted to analyze the difference in the pattern of consumer behaviour before and after the implementation of a severe load shedding program by BESCOM during 2009-10. Data was collected from 113 households during February 2009 and July 2010. The analysis proves that there is indeed a significant difference in the number of uninterrupted power systems (inverters) possessed by households. This could be attributed mainly to the power situation in Karnataka during the same period. The data also confirms the nature of the cost of non-supply curve. The third step in CMI is scenario analysis. Four categories of scenarios are developed based on potential interventions. These are business-as-usual, demand side, supply side and demand-supply side. About 21 scenarios are identified and their results compared. Comparing the four categories of scenarios, it is shown that business-as-usual scenarios may result in exacerbation of the demand-supply gap. Demand side interventions result in savings in the total costs for the community, but cannot aid communities with load shedding. Supply side interventions increase the reliability of the energy system for a small additional cost and communities have the opportunity to even meet their energy needs independent of the grid. The combination of both demand and supply side interventions are the best solution alternative for communities, as they enable communities to meet their energy needs 24/7 in a reliable manner and also do it at a lower cost. With an interactive microgrid implementation, communities have the added opportunity to sell back power to the grid for a profit. The thesis concludes with a discussion of the potential use of IDF in policy making, the potential barriers to implementation and minimization strategies. It presents policy recommendations based on the framework developed and the results obtained.

Energy forms a vital input and critical infrastructure for the economic development of countries and for improving the quality of life of people. Energy is utilized in society through the operation of large socio-technical systems called energy systems. In a growing world, as the focus shifts to better access and use of modern energy sources, there is a rising demand for energy. However, certain externalities result in this demand not being met adequately, especially in developing countries. This constitutes the energy demand – supply matching problem. Load shedding is a response used by distribution utilities in developing countries, to deal with the energy demand – supply problem in the short term and to secure the grid. This response impacts the activities of consumers and entails economic losses. Given this scenario, demand – supply matching becomes a crucial decision making activity. Traditionally demand – supply matching has been carried out by increasing supply centrally in the long term or reducing demand centrally in the short term. Literature shows that these options have not been very effective in solving the demand-supply problem. Gaps in literature also show that the need of the hour is the design of alternate solutions which are tailored to a nation's specific energy service needs in a sustainable way. Microgrids using renewable and clean energy resources and demand side management can be suitable decentralized alternatives to augment the centralized grid based systems and enable demand – supply matching at a local community level. The central research question posed by this thesis is: “How can we reduce the demand – supply gap existing in a community, due to grid insufficiency, using locally available resources and the grid in an optimal way; and thereby facilitate microgrid implementation?” The overall aim of this dissertation is to solve the energy demand – supply matching problem at the community level. It is known that decisions for the creation of energy systems are influenced by several factors. This study focuses on those factors which policy-makers and stakeholders can influence. It proposes an integrated decision framework for the creation of community microgrids. The study looks at several different dimensions of the existing demand – supply problem in a holistic way. The research objectives of this study are: 1. To develop an integrated decision framework that solves the demand – supply matching problem at a community level. 2. To decompose the consumption patterns of the community into end-uses. solar thermal, solar lighting and solar pumps and a combination of these at different capacities. The options feasible for medium income consumers are solar thermal, solar pumps, municipal waste based systems and a combination of these. The options for high income consumers are municipal waste based CHP systems, solar thermal and solar pumps. Residential consumers living in multi-storied buildings also have the options of CHP, micro wind and solar. For cooking, LPG is the single most effective alternative. 3. To identify the ‗best fitting‘ distributed energy system (microgrid), based on the end-use consumption patterns of the community and locally available clean and renewable energy resources, for matching demand – supply at the community level. 4. To facilitate the implementation of microgrids by * Contextualizing the demand – supply matching problem to consider the local social and political environment or landscape, * Studying the economic impact of load shedding and incorporating it into the demand-supply matching problem, and * Presenting multiple decision scenarios, addressing the needs of different stakeholders, to enable dialogue and participative decision making. A multi-stage Integrated Decision Framework (IDF) is developed to solve the demand - supply matching problem in a sequential manner. The first stage in the IDF towards solving the problem is the identification and estimation of the energy needs / end-uses of consumers in a community. This process is called End-use Demand Decomposition (EUDD) and is accomplished by an empirical estimation of consumer electricity demand based on structural and socio-economic factors. An algorithm/ heuristic is also presented to decompose this demand into its constituent end-uses at the community level for the purpose of identifying suitable and optimal alternatives/ augments to grid based electricity. The second stage in the framework is Best Fit DES. This stage involves identifying the “best-fit‘ distributed energy system (microgrid) for the community that optimally matches the energy demand with available forms of supply and provides a schedule for the operation of these various supply options to maximize stakeholder utility. It provides the decision makers with a methodology for identifying the optimal distributed energy resource (DER) mix, capacity and annual operational schedule that “best fits” the given end-use demand profile of consumers in a community and under the constraints of that community such that it meets the needs of the stakeholders. The optimization technique developed is a Mixed Integer Linear Program and is a modification of the DER-CAM™ (Distributed Energy Resources Customer Adoption Model), which is developed by the Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory using the GAMS platform. The third stage is the Community Microgrid Implementation (CMI) stage. The CMI stage of IDF includes three steps. The first one is to contextualize the energy demand and supply for a specific region and the communities within it. This is done by the Energy Landscape Analysis (ELA). The energy landscape analysis attempts to understand the current scenario and develop a baseline for the study. It identifies the potential solutions for the demand - supply problem from a stakeholder perspective. The next step provides a rationale for the creation of community level decentralized energy systems and microgrids from a sustainability perspective. This is done by presenting a theoretical model for outage costs (or load shedding), empirically substantiating it and providing a simulation model to demonstrate the viability for distributed energy systems. Outage cost or the cost of non supply is a variable that can be used to determine the need for alternate systems in the absence/ unavailability of the grid. The final step in the CMI stage is to provide a scenario analysis for the implementation of community microgrids. The scenario analysis step in the framework enlightens decision makers about the baselines and thresholds for the solutions obtained in the “best fit‘ analysis. The first two stages of IDF, EUDD and Best Fit DES, address the problem from a bottom-up perspective. The solution obtained from these stages constitutes the optimal solution from a technical perspective. The third stage CMI is a top-down approach to the problem, which assesses the social and policy parameters. This stage provides a set of satisficing solutions/ scenarios to enable a dialogue between stakeholders to facilitate implementation of microgrids. Thus, IDF follows a hybrid approach to problem solving. The proposed IDF is then used to demonstrate the choice of microgrids for residential communities. In particular, the framework is demonstrated for a typical residential community, Vijayanagar, situated in Bangalore and the findings presented. The End-use Demand Decomposition (EUDD) stage provides the decision makers with a methodology for estimating consumer demand given their socio-economic status, fuel choice and appliance profiles. This is done by the means of a statistical analysis. For this a primary survey of 375 residential households belonging to the LT2a category of BESCOM (Bangalore Electricity Supply Company) was conducted in the Bangalore metropolitan area. The results of the current study show that consumer demand is a function of the variables family income, refrigeration, entertainment, water heating, family size, space cooling, gas use, wood use, kerosene use and space heating. The final regression model (with these variables) can effectively predict up to 60% of the variation in the electricity consumption of a household ln(ElecConsumption) = 0.2880.396*ln(Income)+0.2 66*Refri geration+ 0.708*Entertainment+0.334*WaterHeating+0.047*FamSize+ 0243*SpaceCooling.+580*GasUse+0.421*WoodUse–0.159*KeroseneUse+ 0.568*SpaceHeating ln(ElecConsumption) = 0.406*ln(Income)0.168*Ref rigeration+0.139*Entertainment+ 0.213*WaterHeating+0.114*FamSize+0.121*SpacCooling+0.171*GasUse+ 0.115*WoodUse–0.094*KeroseneUse+0.075*SpaceHeating   The next step of EUDD is to break up the demand into its constituent end-uses. The third step involves aggregating the end-uses at the community level. These two steps are to be performed using a heuristic. The Best Fit DES stage of IDF is demonstrated with data from an urban community in Bangalore. This community is located in an area called Vijayanagar in Bangalore city. Vijayanagar is a mainly a residential area with some pockets of mixed use. Since grid availability is the constraining parameter that yields varying energy availability, this constraint is taken as the criteria for evaluation of the model. The Best Fit DES model is run for different values of the grid availability parameter to study the changes in outputs obtained in DER mix, schedules and overall cost of the system and the results are tabulated. Sensitivity analysis is also performed to study the effect of changing load, price options, fuel costs and technology parameters. The results obtained from the BEST Fit DES model for Vijayanagar illustrate that microgrids and DERs can be a suitable alternative for meeting the demand – supply gap locally. The cost of implementing DERs is the optimal solution. The savings obtained from this option however is less than 1% than the base case due to the subsidized price of grid based electricity. The corresponding costs for different hours of grid availability are higher than the base case, but this is offset by the increased efficiency of the overall system and improved reliability that is obtained in the community due to availability of power 24/7 regardless of the availability of grid based power. If the price of grid power is changed to reflect the true price of electricity, it is shown that DERs continue to be the optimal solution. Also the combination of DERs chosen change with the different levels of non-supply from the grid. For the study community, Vijayanagar, Bangalore, the DERs chosen on the basis of resource availability are mainly discrete DERs. The DERs chosen are the LPG based CHP systems which run as base and intermediate generating systems. The capacity of the discrete DERs selected, depend on the end-use load of the community. Biomass based CHP systems are not chosen by the model as this technology has not reached maturity in an urban setup. Wind and hydro based systems are not selected as these resources are not available in Vijayanagar. The CMI stage of IDF demonstrates the top-down approach to the demand-supply matching problem. For the Energy Landscape Analysis (ELA), Bangalore metropolis was chosen in the study for the purpose of demonstration of the IDF framework. Bangalore consumes 25% of the state electricity supply and its per capita consumption at 1560kWh is higher than the state average of 1230kWh and is 250% more than the Indian average of 612kWh. A stakeholder workshop was conducted to ascertain the business value for clean and renewable energy technologies. From the workshop it was established that significant peak power savings could be obtained with even low penetrations of distributed energy technologies in Bangalore. The feasible options chosen by stakeholders for low income consumers are The second step of CMI is finding an economic rationale for the implementation of community microgrids. It is hypothesized that the ‘The cost of non-supply follows an s-shaped curve similar to a growth curve.’ It is moderated by the consumer income, consumer utility, and time duration of the load shedding. A pre and post event primary survey was conducted to analyze the difference in the pattern of consumer behaviour before and after the implementation of a severe load shedding program by BESCOM during 2009-10. Data was collected from 113 households during February 2009 and July 2010. The analysis proves that there is indeed a significant difference in the number of uninterrupted power systems (inverters) possessed by households. This could be attributed mainly to the power situation in Karnataka during the same period. The data also confirms the nature of the cost of non-supply curve. The third step in CMI is scenario analysis. Four categories of scenarios are developed based on potential interventions. These are business-as-usual, demand side, supply side and demand-supply side. About 21 scenarios are identified and their results compared. Comparing the four categories of scenarios, it is shown that business-as-usual scenarios may result in exacerbation of the demand-supply gap. Demand side interventions result in savings in the total costs for the community, but cannot aid communities with load shedding. Supply side interventions increase the reliability of the energy system for a small additional cost and communities have the opportunity to even meet their energy needs independent of the grid. The combination of both demand and supply side interventions are the best solution alternative for communities, as they enable communities to meet their energy needs 24/7 in a reliable manner and also do it at a lower cost. With an interactive microgrid implementation, communities have the added opportunity to sell back power to the grid for a profit. The thesis concludes with a discussion of the potential use of IDF in policy making, the potential barriers to implementation and minimization strategies. It presents policy recommendations based on the framework developed and the results obtained.

The increasing complexity of the current dynamic business environment makes some of centralized decision making either difficult or inefficient. While some attention has been paid to the dynamic distributed decision making (DDM), the research on decision support systems (DDS) supporting DDM is quite limited. In particular, how to model the structure of dynamic DDM and use information technology to support dynamic DDM remains as a critical question. In this thesis, from information processing prospective, we propose a conceptual model, i.e. integrated decision stations (IDS), to address how to support dynamic DDM. Our model is based on the decomposition of decision criteria and information flows. To demonstrate the applicability of this framework, we apply it to lead time management and illustrate it with a prototype. It shows that our framework is powerful to describe various scenarios of DDM. In addition, we conduct a simulation study to investigate the impacts of two distinct features of IDS, i.e. real-time information and information coordination, on the decision performance. The results partially support that both information delay and information coordination have significant impacts on decision performance. The contribution of our study is that it provides both practitioners and academic researchers with a comprehensive framework to design effective DDM support systems and study their impacts on decision performance

碩士
南華大學
資訊管理學研究所
94
In recent years, the Web is developing to speed up the dissemination of information. Customers usually make shopping decision by referring to the information from the Web. However, applications like shopping websites, shopping Netnews, and virtual communities on the Web are currently not integrated together very well. It results in inconvenience while customers search the shopping information from the Web. Although some shopping websites combine the functions of shopping, discussion, and evaluation, this kind of integration is only limited to the websites themselves, and it does not integrate all relevant information on the Web. 　 　　To solve the above problem, we design a system framework to combine Meta Web Service (MWS), DAML-S/UDDI Matchmaker, and DAML-S Virtual Machine to build an Integrated Shopping Decision Information Framework (ISDIF), which is an MWS-based framework to include information from shopping websites and virtual communities. Customers can make a shopping decision by referring to the information from ISDIF. 　 　　Web Services technology is an XML-based architecture to achieve interoperability and portability. The major focus of MWS is the application of Semantic Web Services, which can organize relevant information on the Web. Also, it will be easier to acquire and share the relevant resources and services on the Web by building Ontology. MWS is like an Intelligent Agent, it can realize automatic discovery and automatic integration to satisfy the users'' demand.

碩士
國立中山大學
公共事務管理研究所
103
The purpose of this research is to classify the theories of judgment and decision-making. Using the main concepts and purposes from those theories to construct a framework to define judgment domain, decision-making domain and mixture domain. By doing this, we can distinguish the differences of those theories easier and comprehend the applicability and development trend. Additionally, we did an inquiry via the main concepts to survey the judgment and decision-making integrated framework, to ensure the generality and comprehensiveness of it. Afterward we can treat public affairs with multiple perspectives in this society with risk and uncertainty by using j-d integrated framework.

博士
國立清華大學
工業工程與工程管理學系
100
Many enterprises would invest new business for sustainable revenue growth or profitability. However, the new business investment is not always profitable to enterprises as expected. Some investments may cause serious financial loss due to wrong business selection or poor operation strategy decision. Thus, the decisions on new business evaluation and operation strategy are crucial to enterprises. This research aims to propose an integrated decision framework named BOSSUP (Business and Operation Strategy Support with UNISON and PDCCCR) for the new business evaluation and operation strategy decision. The proposed framework applied UNISON decision analysis process to evaluate the new business in three phases: business strategy formulation, new business selection, and operation strategy decision. It is a comprehensive process model instead of pure valuation and selection model only, and it could help enterprises to start the evaluation smoothly and easier to make right decision at right time. Besides, this study developed a set of analytic models to clarify the key business strategy and operation strategy concerns and interactions according to the PDCCCR concept structure. It could be used for strategy group analysis, visualized sensitivity analysis for the interactions among key operation focuses, and integrated with a multi attributes decision method named AHP+ROC. A case study was conducted to show how a semiconductor company evaluated the new MEMS business. It demonstrated the visibility of BOSSUP framework and related analytic methods.

"Canada's municipal infrastructure is at risk." This was the key finding of Canada’s first municipal infrastructure report card. Given the current state of risk for Canadian infrastructure, municipalities face challenging decisions for planning the integrated repair/renewal of road, water and sewer networks. Decision-making surrounding the assets in these networks requires data collection, analysis, the identification of decision variables and undertaking optimized decision-making processes. Currently there is a lack of tools available to simplify the decision making process for stakeholders. The research objective is to establish a methodology and framework that facilitates decision-making processes used during corridor rehabilitation project planning. The proposed framework consists of three main models: (1) Risk assessment, (2) Performance evaluation and (3) Integrated decision support system (IDSS). The risk model was developed using a mixed Delphi-Analytical Hierarchy Process approach. The impacts of four main consequences of failure with eighteen sub factors were considered. Road, water and sewer networks indices were amalgamated and grouped into an overall integrated risk index using K-means Clustering technique. The performance model considers nine factors that represent the asset performance. These factors were mapped using fuzzy logic technique to a Customer Driven Performance Measure (CDPM) index. The IDSS framework allows the setting of priorities for integrated corridor rehabilitation and implementing optimization via Integer Programming. Finally, these models were applied in a prototype tool using Visual Basic built on Microsoft Access, Excel and GIS platforms. A series of workshop interviews were conducted with various municipalities to collect the necessary information. Data provided by the City of Guelph was used in a case study in order to demonstrate the model features. Results show that Pipe/road size and accessibility factors had the highest impact on the integrated risk index. The road roughness rating and watermain breaks results show the highest impact on the CDPM index. Optimization outcomes demonstrated that corridor rehabilitation alternatives resulted in a ‘maximum risk reduced per dollar spent’. The developed models can be used by researchers and practitioners (municipal engineers and consultants) in order to prioritize corridor rehabilitation projects thereby easing the challenge faced by stakeholders regarding the future of municipal infrastructure.

碩士
國立臺灣大學
氣候變遷與永續發展國際學位學程
107
After the industrial revolution, human''s economic development is growing with a large amount of greenhouse gas emissions. The human influence on climate change cause different kinds of climate risks increasing, and here come much more challenges about sustainable development than ever, while various extreme weather events are happening. Therefore, climate adaptation makes people to prepare as enough as possible for the impact of climate change and to reduce the risk to sustainable development. It also emphasized the importance of climate change and sustainable development issues to human, and people have to accelerate the climate actions in The Paris Agreement and 2030 Agenda in 2015. However, it needs complete accessing progress tp know the interaction between the factors of issues to make sure the relationship of decision-making. Thereby, this study provides an integrated decision-making framework, AdaptSDGs, for climate adaptation and 17 Sustainable Development Goals (SDGs) from 2030 Agenda. Moreover, AdaptSDGs aims to develop the accessing methods and tools for interdisciplinary, interdepartmental, diversified adaptation plans with its national conditions to ensure the adaptation plans would not lead to deviation from sustainable development.AdaptSDGs includes four climate adaptation accessing steps with the approach of SDGs (identifying problems and goals, assessing current climate risk, assessing future climate risk, identifying adaptation options) and a tool kit with four supporting tools (climate risk templates, research method tree, key targets interaction system, and risk factor interaction system) to build up systematic scientific analysis methods and processes for the scientific supports on the decision-making of climate adaptation and SDGs. This study takes Water supply and demand balance, the critical issue of SDG 6 in Taiwan to demonstrate how to do climate adaptation assessments with AdaptSDGs — deconstructing climate risk factors of the critical issue with climate risk template; research method tree guides to research the interaction of SDG 6 in Taiwan by "expert questionnaire"; the result of export questionnaire is used to build up the Key Targets Interaction System (KTIS) with system dynamic tool, Vensim; Key Targets Interaction System (KTIS) helps to set up to address the trade-offs and synergies between SDG targets so as to reduce the conflicts between SDG targets from climate adaptation plans and to increase the benefits of climate adaptation to sustainable development; risk Factor Interaction System (RFIS) aims to assess the impact of climate risk on the performance of SDGs of critical issues, thereby adding climate change factors to the 2030 target of national SDGs to ensure the rationality of target setting with Vensim. Assessing the compliance of the Taiwan''s regional water resources adaptation program with key sub-targets "6.4: Improving water efficiency, ensuring sustainable access and supply of fresh water", "6.1: Universal access to safe drinking water", "6.2: Appropriate for everyone and Fair sanitary conditions", "6.5: Integrated water resources management at all levels", "6.b: Support and strengthen local community participation in improving water and sanitation management", "1.a: Providing sufficient capacity for developing countries "Executing related plans and policies for all poverty", "11.1: Access to affordable housing and basic services for all" has a significant positive impact, but results in "8.2: Developing high value-added and labor-intensive industries To promote the negative development of economic productivity. This study proposes AdaptSDGs as a decision-making integration framework for climate adaptation and sustainable development goals. Although there are some unsatisfactory tools in the construction of the tool, after the case study, we can grasp the improvement, and hope for continuous improvement in the future to help complete the climate — scientific analysis of adaptation and SDGs decision making.

Product life cycle (PLC) is the cycle which every product goes through from introduction to eventual demise. There are several issues with the current life cycle of a product when looked from the environmental impact perspective. These are: 1) depletion of natural resources due to the use of virgin materials for production, 2) Consumption of substantial amounts of energy during manufacturing, assembly and use, and 3) production of large amounts of waste during the lifecycle including those at the End of Life (EoL) phase. These issues impact resource scarcity, adverse effects on the environment and loss of embodied energy as waste. Some of the potential solutions to these issues, as proposed in literature, are: to recycle, reuse and remanufacture products in order to reclaim materials, components and sub-assemblies from used products and make them available for new products. In order to efficiently carry out these recovery processes, a pre-requisite is disassembly. Product disassembly is defined as the processes of systematic removal of desirable constitute parts from an assembly while ensuring that there is no impairment of the parts due to the disassembly process. The following are the major research issues in the field of disassembly. One is the conflict between environmental and economic goals, i.e. as to which should be targeted at in disassembly objectives. These conflicts lead to abandoning non-destructive disassembly techniques so as to favour the profit objective. The other issues, prevalent during EoL phase, are: corrosion due to use, less residual value in the parts, complicated structure and intricacy in parts, which together make non-destructive disassembly a task difficult for automation. This means that disassembly processes have to be carried out by human operators. The manual disassembly processes are effort intensive and pose ergonomic risks to the human operators involved in disassembling. The nature of ergonomic risks and effort spent in disassembly is influenced by the efficiency of disassembly operation. However, little research has been carried out to address the above factors of effort, profit, efficiency, environment and ergonomic risk during disassembly in an integrated manner. These factors form the major motivations for the research work carried out in this thesis. A series of empirical studies have been undertaken to assess these factors and their impact on product disassembly. The studies focus on disassembly processes for consumer electronic products in two major recycling sectors in developing countries, leading to development of metrics with which the above factors can be assessed individually and traded off in an integrated manner during the early design stages of a product. These metrics should help designers understand and improve the major disassembly aspects of a product during designing and help prevent major disassembly problems at the EoL phase while improving efficiency of recovery options. The objective of this thesis, therefore, is to develop an Integrated Framework for supporting decision making during early stages of design to improve disassembly during the EoL phase of the product. The framework is intended to help in evaluating alternative designs for easy (less effort), profitable, efficient and environment-friendly disassembly at the EoL phase of the product life cycle. The Framework constitutes new measures developed for supporting decision making on above aspects of disassembly during the early stage of designing. The Framework has been implemented into a computer based tool called ‘IdeAssemble’ and evaluated for its functionality with the help of a design experiment. The tool can be used at the embodiment stage of the design phase, when on an exploded view of the product, with information on its materials, geometry, disassembly tools and types of disassembly task are available to the designer.

Product life cycle (PLC) is the cycle which every product goes through from introduction to eventual demise. There are several issues with the current life cycle of a product when looked from the environmental impact perspective. These are: 1) depletion of natural resources due to the use of virgin materials for production, 2) Consumption of substantial amounts of energy during manufacturing, assembly and use, and 3) production of large amounts of waste during the lifecycle including those at the End of Life (EoL) phase. These issues impact resource scarcity, adverse effects on the environment and loss of embodied energy as waste. Some of the potential solutions to these issues, as proposed in literature, are: to recycle, reuse and remanufacture products in order to reclaim materials, components and sub-assemblies from used products and make them available for new products. In order to efficiently carry out these recovery processes, a pre-requisite is disassembly. Product disassembly is defined as the processes of systematic removal of desirable constitute parts from an assembly while ensuring that there is no impairment of the parts due to the disassembly process. The following are the major research issues in the field of disassembly. One is the conflict between environmental and economic goals, i.e. as to which should be targeted at in disassembly objectives. These conflicts lead to abandoning non-destructive disassembly techniques so as to favour the profit objective. The other issues, prevalent during EoL phase, are: corrosion due to use, less residual value in the parts, complicated structure and intricacy in parts, which together make non-destructive disassembly a task difficult for automation. This means that disassembly processes have to be carried out by human operators. The manual disassembly processes are effort intensive and pose ergonomic risks to the human operators involved in disassembling. The nature of ergonomic risks and effort spent in disassembly is influenced by the efficiency of disassembly operation. However, little research has been carried out to address the above factors of effort, profit, efficiency, environment and ergonomic risk during disassembly in an integrated manner. These factors form the major motivations for the research work carried out in this thesis. A series of empirical studies have been undertaken to assess these factors and their impact on product disassembly. The studies focus on disassembly processes for consumer electronic products in two major recycling sectors in developing countries, leading to development of metrics with which the above factors can be assessed individually and traded off in an integrated manner during the early design stages of a product. These metrics should help designers understand and improve the major disassembly aspects of a product during designing and help prevent major disassembly problems at the EoL phase while improving efficiency of recovery options. The objective of this thesis, therefore, is to develop an Integrated Framework for supporting decision making during early stages of design to improve disassembly during the EoL phase of the product. The framework is intended to help in evaluating alternative designs for easy (less effort), profitable, efficient and environment-friendly disassembly at the EoL phase of the product life cycle. The Framework constitutes new measures developed for supporting decision making on above aspects of disassembly during the early stage of designing. The Framework has been implemented into a computer based tool called ‘IdeAssemble’ and evaluated for its functionality with the help of a design experiment. The tool can be used at the embodiment stage of the design phase, when on an exploded view of the product, with information on its materials, geometry, disassembly tools and types of disassembly task are available to the designer.

abstract: One of the key infrastructures of any community or facility is the energy system which consists of utility power plants, distributed generation technologies, and building heating and cooling systems. In general, there are two dimensions to “sustainability” as it applies to an engineered system. It needs to be designed, operated, and managed such that its environmental impacts and costs are minimal (energy efficient design and operation), and also be designed and configured in a way that it is resilient in confronting disruptions posed by natural, manmade, or random events. In this regard, development of quantitative sustainability metrics in support of decision-making relevant to design, future growth planning, and day-to-day operation of such systems would be of great value. In this study, a pragmatic performance-based sustainability assessment framework and quantitative indices are developed towards this end whereby sustainability goals and concepts can be translated and integrated into engineering practices. New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components. Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance. A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
Dissertation/Thesis
Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018

Yes
This study examines the effect of big data powered artificial intelligence on customer knowledge creation, user knowledge creation and external market knowledge creation to better understand its impact on B2B marketing rational decision making to influence firm performance. The theoretical model is grounded in Knowledge Management Theory (KMT) and the primary data was collected from B2B companies functioning in the South African mining industry. Findings point out that big data powered artificial intelligence and the path customer knowledge creation is significant. Secondly, big data powered artificial intelligence and the path user knowledge creation is significant. Thirdly, big data powered artificial intelligence and the path external market knowledge creation is significant. It was observed that customer knowledge creation, user knowledge creation and external market knowledge creation have significant effect on the B2B marketing-rational decision making. Finally, the path B2B marketing rational decision making has a significant effect on firm performance.
The full-text of this article will be released for public view at the end of the publisher embargo on 23 Dec 2022.

Abstract in English, Zulu and Afrikaans
The primary intent of this study was to develop a competitive intelligence (CI) programme implementation strategy framework for the effective use of CI in strategic decision-making (SDM) in a conglomerate, using embedded multiple units and a single-case exploratory study that is qualitative dominant. The study therefore explored the strategic value of CI for SDM in a company that has a conglomerate structure and whose subsidiaries are vertically integrated. Despite the perceived usefulness of CI for distinctive SDM, the case conglomerate and its subsidiaries had collected and employed the available CI products to support their strategic, tactical and other business decisions. Overall results indicated differences between the subsidiaries and the headquarter; and among the subsidiaries on CI practice (CI collection, CI coordination, CI sharing and CI effort) and CI usage for SDM and other decisions. Although a similar strategy development process (guided by the grand corporate strategy), management structure, decision-making process and orientation in the subsidiaries existed, these uniformities did not significantly result in a uniform level of application and usage of CI for SDM across the conglomerate. The conclusion is that CI application is very subjective and contextual even in a vertically integrated conglomerate. Through theory, literature review and empirical findings, synthesis and iteration, a middle-range theory that integrates the CI and SDM disciplines in terms of the contextual issues both share is also constructed. The study also developed a novel way of crafting CI for SDM, which may fit into the existing structure and realities of the conglomerate so as to formalise CI. The CI programme implementation strategy framework was developed considering the proof of tested theories, best practices, existing context, strategy, decision-making process, structure, enabling factors and capabilities of the conglomerate. The CI programme implementation strategy framework, accompanied by a proposed CI structure, has immediate pragmatic utility. It could enable the conglomerate to initiate a formal CI programme without delay and to develop it following an organisational maturation cycle. The study makes an original contribution by conceptualising a CI programme implementation strategy for a unique case and theorising the case within a novel extension within middle-range theory (“SDM and CI application can be viewed in the contextual domains both share”). The exploratory study itself, which led to merging theory and best practices with empirical results and fitting the theories and best practices into case conglomerate’s realities, also makes the study unique in terms of its approach and outputs.
Inhloso enkulu yalolu cwaningo kwakungukusungula uhlaka lokuqala ukusebenzisa uhlelo lwamasu obuhlakani bokuqhathanisa izinkampani ezincintisanayo, obaziwa ngokuthi yiCompetitive Intelligence (iCI) ngesiNgisi ukuze isebenze kahle ekuthathweni kwezinqumo ezihambisana namasu okwaziwa ngestrategic decision-making (iSDM) ngesiNgisi kwinhlanganyela yezinkampani, kusetshenziswa uhlobo locwaningo olungamayunithi amaningi afakwe ndawonye, oluhlola udaba olulodwa nolugxile kakhulu ekuqoqweni kwemininingwane. Ngakhoke, lolu cwaningo luhlole umthelela omuhle wamasu eCI ngokuthatha izinqumo ezihambisana namasu (iSDM) enkampanini enomumo wenhlanganyela yezinkampani enezinkampani ezingena ngaphansi kwayo ezenza imisebenzi eyahlukahlukene. Phezu kokumsebenzi obonakalayo weCI ngokuhlukile kwiSDM, inhlangayela yezinkampani okuyiyo ebhekiwe kanye nezinkampani ezingaphansi kwayo yaqoqa yase isebenzisa imikhiqizo yeCI etholakalayo ukusingatha ukuthatha kwayo izinqumo ezihambisana namasu, namaqhinga kanye nezinye izinqumo zebhizinisi. Imiphumela ephelele yabonisa ukuthi kukhona ukungafani phakathi kwezinkampani ezingena ngaphansi kwayo kanye nekomkhulu; kanti futhi phakathi wezinkampani ezingena ngaphansi kwayo kokuphathelene neCI (Ukuqoqwa kwemininingwane yeCI, ukuhlanganiswa kwemininingwane yeCI, ukusabalalisa imininingwane yeCI nokusebenza kweCI) nokusetshenziswa kweSDM nezinye izinqumo. Nakuba kwakukhona inqubo yokuthuthukisa isu elifanayo (elandela imigomo yesu elihle lenkampani), ukwakheka kohlaka lwabaphethe, inqubo yokuthatha izinqumo kanye nokuqondiswa kwezinkampani ezingaphansi kwenye, lokhu kwefaniswa akuzange kube ngokufanayo endleleni yokwenza nokusebenziswa kweCI kwiSDM kwinhlangayela yezinkampani. Isiphetho ukuthi uhlelo lokusebenza lweCI luncike kakhulu ohlangothini nasengqikithini eyodwa kwinhlanganyela yezinkampani ezenza izinto ezahlukahlukene. Ngokulandela ukuhlaziywa kwemibhalo yemibono yezinzululwazi, kanye nokutholakele uma kwenziwa ucwaningo olubheka izinto ngenkathi zenzeka, ukuhlanganiswa kwemininingwane kanye nokuphindaphindwa kokuhlolwa, kuphinde kwakhiwe imibono yezinzululwazi emibili ehlanganisa imikhakha yeCI neSDM maqondana nezingqikithi ezifanayo kuyona. Ekugcineni, ucwaningo luphinde lwasungula indlela engakaze ibe khona yokwakha iCI iyakhela iSDM engangena ithi khaxa ekwakhekeni nasesimweni esikhona senhlanganyela yezinkampani ukuze iCI ihleleke ngokusemthethweni. Uhlaka lwesu lokuqaliswa kokusebenza kohlelo lweCI lwenziwa ngoba kucatshangwa ngobufakazi obutholakala kwimibono yezinzululwazi ehloliwe, okusebenze ngempumelelo, indikimba ekhona njengamanje, isu, inqubo yokuthatha izinqumo, ukwakheka, yilokho okwenza izinto zenzeke futhi kusebenzeke kwinhlanganyela yezinkampani. Uhlaka lwesu lokuqaliswa kokusebenza kohlelo lweCI, oluphelezelwa ukwakheka okuhlongoziwe kweCI kukwazi ukuhlolisisa kahle umqondo wokukwazi ukubona ubungako bolwazi nesidingo solunye ucwaningo. Kungasiza inhlanganyela yezinkampani, cishe, ukuba ikwazi ukuqala uhlelo olusha lweCI nokulithuthukisa kulandela uchungechunge lwendlela yokukhula yenhlangano. Ucwaningo lufaka ulwazi olusha esivivaneni ngokuqhamuka nomqondo omusha wesu lokuqala ukusebenzisa uhlelo lweCI odabeni olungajwayelekile, bese lubeka imibono ngodaba olubhekwayo ngendlela engakaze yenzeke nehlanganisa imibono yezinzululwazi kanye nocwaningo olubheka izinto ngenkathi zenzeka (“Ukusetshenziswa kweSDM neCI kungabhekwa ezizindeni zengqikithi ezifanayo kukona”). Ucwaningo oluhlolayo, lona uqobo, oluholela ekuhlanganisweni kwemibono yezinzululwazi nokubhekwa kwalokho okucwaningwayo ukuthi kusebenza kahle kuphi kanye nemiphumela yocwaningo olubheka izinto ngenkathi zenzeka, nokuhlanganisa lokho nokwenzeka ngempela enhlanganyeleni yezinkampani, nakho kwenza lolu cwaningo lube ngolwehlukile maqondana nendlela oluyilandelayo kanye nemiphumela evelayo.
Die primêre doel van hierdie studie was om 'n strategieraamwerk vir programimplementering van mededingingsintelligensie (MI) te ontwikkel vir die doeltreffende gebruik van MI in strategiese besluitneming in 'n konglomeraat, deur 'n vasgelegde veelvoudige eenhede, enkelgeval-verkenningstudie, wat ook kwalitatief dominant is, te gebruik. Die studie het dus die strategiese waarde van MI vir strategiese besluitneming verken in 'n maatskappy wat 'n konglomeraatstruktuur het en wie se filiale vertikaal geïntegreer is. Ondanks die waargenome nuttigheid van MI vir spesifiek strategiese besluitneming, het die gevallestudiekonglomeraat en sy filiale die beskikbare MI-produkte versamel en aangewend om hul strategiese, taktiese en ander sakebesluite te ondersteun. Algehele resultate het die bestaan van verskille tussen die filiale en die hoofkantoor aangedui; en tussen die filiale oor MI-praktyke (MI-versameling, MI-koördinering; MI-deling en MI-pogings) en MI-gebruik vir strategiese en ander besluite. Alhoewel daar soortgelyke strategiese ontwikkelingsprosesse bestaan (gelei deur die groot korporatiewe strategie), het hierdie eenvormigheid in bestuurstrukture, besluitnemingprosesse en oriëntering in die filiale nie 'n beduidende eenvormige vlak van toepassing en gebruik van MI vir strategiese besluitneming regdeur die konglomeraat tot gevolg gehad nie. Gevolglik is MI-toepassing baie subjektief en kontekstueel, selfs in 'n konglomeraat wat vertikaal geïntegreer is. Deur teoretiese, literatuuroorsig- en empiriese bevindinge is sintese en iterasie, twee middelvlakteorieë, ook saamgestel wat velde van MI en strategiese besluitneming met betrekking tot die kontekstuele kwessies wat albei deel, geïntegreer het. Op die ou end het die studie ook 'n nuwe manier ontwikkel om MI vir strategiese besluitneming te bewerk wat by die bestaande struktuur en realiteite van die konglomeraat kan inpas om MI te formaliseer. Die strategieraamwerk vir programimplementering van MI is ontwikkel met die bewys van getoetste teorieë, beste praktyke, bestaande konteks, strategie, besluitnemingsproses, faktore wat strukture moontlik maak en vermoë van die konglomeraat, in gedagte. Die strategieraamwerk vir programimplementering van MI, saam met die voorgestelde MI-strukture, het onmiddellike pragmatiese nut. Dit kan die konglomeraat onmiddellik in staat te stel om 'n formele MI-program te inisieer en dit te ontwikkel deur 'n organisatoriese verouderingsiklus te volg. Die studie maak 'n oorspronklike bydra deur 'n strategie vir programimplementering van MI te konseptualiseer vir 'n unieke geval, die teoretisering van die geval binne 'n nuwe uitbreiding in 'n middelvlakteorie ("Toepassing van strategiese besluitneming en MI kan in die kontekstuele domeine beskou word wat beide deel"). Die verkenningstudie self, wat tot die samesmelting van teorie en beste praktyke met die empiriese resultate gelei het en die passing van die teorieë en beste praktyke in die gevallestudiekonglomeraat se realiteite, maak die studie ook uniek met betrekking tot sy benadering en opbrengs.
Graduate School for Business Leadership
D.B.L.