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MacLean, Thomas Frank. "Asymmetric demand for energy : a cointegration approach /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/7494.
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Bowbrick, Peter. "A critique of Lancaster's approach to the economics of quality : an agricultural economics approach." Thesis, Brunel University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239098.
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Ertem. "Demand Driven Disassembly Planning." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608169/index.pdf.
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In this thesis, we deal with the demand driven disassembly planning. The main aim of the study is to construct heuristic approaches according to the suggested improvements in the literature. These heuristic approaches are further improved by recognizing the key points of the disassembly planning problem. All of the solution approaches aim minimizing total cost related to relevant costs of disassembly operations. Another subject given attention in this thesis is the importance of the setup cost on the disassembly planning, which has not been studied yet in the literature to the best of our knowledge. Computational studies are carried out to assess the performance of the heuristic procedures proposed.
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TORRINI, FABIANO CASTRO. "LONG-TERM ELECTRICITY DEMAND FORECAST BY FUZZY LOGIC APPROACH." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26974@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>O consumo de energia elétrica no Brasil tem sido amplamente discutido nos últimos tempos. A crise do abastecimento de energia em 2001, fez com que o Governo Federal tomasse uma série de medidas para tentar corrigir os erros do modelo em vigência. Hoje, entende-se que a situação do setor energético é delicada, fazendo com que o risco de um novo racionamento volte a ser considerado. Neste contexto, as companhias de energia estão se deparando com o desafio de obter previsões de carga mais precisas. Consequentemente, uma vez que esta demanda encontra-se inserida em um cenário instável de economia, estas estimativas requerem métodos mais eficientes e inovadores. O objetivo principal deste estudo é fornecer uma nova abordagem para o problema de previsão do consumo de eletricidade. A metodologia de lógica fuzzy é proposta com o objetivo de extrair regras das variáveis de entrada e fornecer previsões de longo prazo para a demanda de eletricidade no Brasil. Através da modelagem estatística, a identificação das estruturas de dependência e defasagens entre estas variáveis, fornece suporte para os modelos independentes com previsões anuais. A grande vantagem dos modelos de lógica fuzzy vem da habilidade destes de imitar o pensamento humano em cenários de incerteza e imprecisão. Na literatura recente, a formulação destes tipos de modelo tem se limitado a tratar as variáveis explicativas de maneira univariada, ou então envolvendo somente o PIB. Este trabalho propõe a extensão do modelo desenvolvido na literatura, começando com variáveis como a população do Brasil e o valor adicionado do PIB por estados e setores, juntamente com suas variações. Com isso, o modelo proposto será comparado com a formulação oficial vigente fornecida pela EPE.<br>The consumption of electricity in Brazil has been widely discussed recently. The energy supply crisis in 2001 forced the Federal Government to take a series of measures trying to fix the actual model. Nowadays, it is understood that the energy sector is going through bad times, making the risk of a new rationg plan be considered. In this context, energy companies are facing the challenge of making more accurate load forecast. Consequently, once this need is inserted into a scenario of unstable economy, these estimates require efficient methods combined with innovative features.The aim of this study is to provide a new approach to this electricity prediction problem. A Fuzzy logic methodology is proposed in order to extract rules from the input variables and provide Brazil s Long-term annual electricity demand forecasts. From a statistical modeling point of view, an identification of dependence and lags structure between the input variables provide support for independent models with annual estimates. The advantage of the fuzzy logic model lies on the ability to mimic the human thinking in an environment of uncertainty and imprecision. In recent literature, the formulation of these types of models has been limited to treating the explanatory variables in the univariate form, or involving only the GDP. This study proposes an extension of this model, starting with the Brazilian population and the additional value of the state GDP by sectors with their variations. Then, the proposed model is compared with the official formulation provided by EPE.
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Bowman, John L. (John Lawrence). "The day activity schedule approach to travel demand analysis." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/16731.
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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1998.<br>Includes bibliographical references (p. 181-184) and index.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>This study develops a model of a person's day activity schedule that can be used to forecast urban travel demand. It is motivated by the notion that travel outcomes are part of an activity scheduling decision, and uses discrete choice models to address the basic modeling problem-capturing decision interactions among the many choice dimensions of the immense activity schedule choice set. An integrated system of choice models represents a person's day activity schedule as an activity pattern and a set of tours. A pattern model identifies purposes, priorities and structure of the day's activities and travel. Conditional tour models describe timing, location and access mode of on-tour activities. The system captures trade-offs people consider, when faced with space and time constraints, among patterns that can include at-home and on-tour activities, multiple tours and trip chaining. It captures sensitivity of pattern choice to activity and travel conditions through a measure of expected tour utility arising from the tour models. When travel and activity conditions change, the relative attractiveness of patterns changes because expected tour utility changes differently for different patterns. An empirical implementation of the model system for Portland, Oregon, establishes the feasibility of specifying, estimating and using it for forecasting. Estimation results match a priori expectations of lifestyle effects on activity selection, including those of (a) household structure and role, such as for females with children, (b) capabilities, such as income, and (c) activity commitments, such as usual work levels.<br>(cont.) They also confirm the significance of activity and travel accessibility in pattern choice. Application of the model with road pricing and other policies demonstrates its lifestyle effects and how it captures pattern shifting-with accompanying travel changes-that goes undetected by more narrowly focused trip-based and tour-based systems. Although the model has not yet been validated in before-and-after prediction studies, this study gives strong evidence of its behavioral soundness, current practicality, potential to generate cost-effective predictions superior to those of the best existing systems, and potential for enhanced implementations as computing technology advances.<br>by John L. Bowman.<br>Ph.D.
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Erlandsson, Vilhelm, and Erik Åkerblom. "Demand for Transportationin Circular Businesses : A System Dynamic approach." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300178.
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One of the largest challenges’ mankind is currently facing has been recognized to be climate change. Moving towards climate neutrality, decoupling economic growth from resource use, and at the same time ensuring long-term competitiveness becomes highly important. A possible path to decrease our impact on the environment is to switch from linear to circular material flows, which is today referred to as a circular economy. In a circular economy, assets that are being reused will induce a demand for transportation. Understanding how the transportation demand could be affected is important, since the sector is widely known through its environmental impact causing impaired life expectancy in many parts of the world. This study examines therefore variables in circular businesses that could affect transportation demand both directly and indirectly. These variables have been identified by interviewing eight businesses that employ repair & reuse configurations in a circular context. The study concludes that transportation could be affected in numerous ways, depending on the system's future development. If the current linear paradigm still governs the original equipment manufacturers (OEMs), it will be hard to increase the amount of viable products circulating in the system. The current paradigm has been recognized to be a large barrier due to the high uncertainty of OEMs continuance in a transition to a circular economy. If OEM collaboration could be increased extensively, the system could increase its growth. Further, customer behaviour has also been identified to be a driver for both increasing and decreasing transportation in the system. Increasing the amount of viable products circulating in a circular system comes naturally, as the trade-off in Co2-emissions between increased transportation and newly produced products is prominent. Having such a holistic view argues for the implementation, but the system still has implications regarding sustainability. As the trade-off is continuously made, demand for transportation will be increasing as the system grows. Looking at this from the perspective of the transportation industry, such implementation could make it harder to decrease its Co2-emissions with 70% by 2030, which is the goal set by the Swedish government.<br>De pågående klimatförändringarna är en av vår tids största utmaningar. Att minska resursanvändningen och samtidigt bibehålla samhällets ekonomiska tillväxt ses därför som väsentligt för att nå ökad klimatneutralitet. Till följd av detta har den cirkulära ekonomin utvecklats där linjära produktflöden ersätts av cirkulära. Skiftet till cirkulära flöden kommer troligen bidra till ett nytt transportbehov då produkter i större utsträckning byter användare. Att förstå och kunna redogöra hur det uppkomna transportbehovet ser ut är av betydelse då transportsektorn i sig utgör en stor utmaning i arbetet med att minska den totala klimatpåverkan. Denna studie ämnar därför att studera åtta cirkulära företag och dess verksamheter för att identifiera centrala variabler som har en direkt eller indirekt påverkan på behovet av transporter. Studien visar på att transportbehovet kan tänkas påverkas på olika sätt beroende hur det cirkulära systemet utvecklas framöver. Om det linjära paradigmet fortsätter att gynna originaltillverkare, tillika produkttillverkare, kommer det bli svårt för det cirkulära systemet att uppnå några betydande volymer. Det linjära systemet har identifierats vara en barriär då det förblir osäkert till vilken grad produkttillverkare är redo att bidra till de nya cirkulära flödena. Om tillverkare blir mer öppna och möjliggör för externa aktörer att reparera och hantera deras produkter så spås de cirkulära flödena öka. Vidare så har kundbeteende identifierats som en drivande faktor som både kan leda till en ökad och minskad mängd transporter inom det cirkulära systemet. Att öka mängden cirkulerande produkter kommer naturligt eftersom utsläppsnyttan är betydande vid jämförelse av ökade transporter och nytillverkning av produkter. Helhetsperspektivet argumenterar således för att öka cirkulära produktflöden. En ökad mängd cirkulära produkter kan dock innebära stora utmaningar för transportsektorn och dess förmåga att nå de uppsatta klimatmålen.
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Eriksson, Niclas. "Predicting demand in districtheating systems : A neural network approach." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-175082.
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To run a district heating system as efficiently as possible correct unit-commitmentdecisions has to be made and in order to make those decisions a good forecast ofheat demand for the coming planning period is necessary. With a high quality forecastthe need for backup power and the risk for a too high production are lowered. Thisthesis takes a neural network approach to load forecasting and aims to provide asimple, yet powerful, tool that can provide accurate load forecasts from existingproduction data without the need for extensive model building.The developed software is tested using real life data from two co-generation plantsand the conclusion is that when the quality of the raw data is good, the software canproduce very good forecasting results.
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Feehan, Patrick Joseph. "Attendance demand for soccer : a spatial cross-sectional approach." Thesis, University of Salford, 2002. http://usir.salford.ac.uk/26673/.
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The cost of a return journey to a soccer match can often be comparable to, or even exceed, the admission price. However, in spite of the importance of travel costs, previous studies on the demand for live soccer generally exclude travel costs from the analysis. The thesis explores the consequences of this omission and shows that the likely effect is to bias estimates of the ticket price elasticity downwards. The thesis also argues that the previous estimates of the ticket price and income elasticities are likely to be biased due to generic problems with the time series approach and methodological problems with particular pooled studies. To overcome these problems, the travel cost methodology, developed in the economics of outdoor recreation, is adapted to permit analysis of demand relationships in professional soccer. Attendance at Premier League matches is modelled as a function of travel costs and other factors, such as the admission price and consumer income, using data from a national fan survey. From the results, ticket price elasticities are estimated that are more consistent with profit maximisation than previous estimates. Subsequent analysis on the relationship between attendance and income distinguishes between the decision to become a fan and, given that one is a fan, the question of the number of games to attend in a season. The first decision is shown to be positively related to income, via a social class proxy, and the second decision unrelated to income, giving a positive income elasticity of demand.
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Merino, Castelló Anna. "The Demand for Pharmaceutical Drugs: a Theoretical and Empirical Approach." Doctoral thesis, Universitat Pompeu Fabra, 2003. http://hdl.handle.net/10803/7416.
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A pesar de las ventajas económicas que a priori ofrecen los medicamentos genéricos, su tasa de penetración en el territorio nacional no alcanza de cuota de mercado de los correspondientes productos de marca. Una de las justificaciones con más peso en la literatura es la incertidumbre que generan los genéricos entre pacientes y profesionales sanitarios y que les convierten en reacios a cambiar de un medicamento de marca de esta baja penetración de los genéricos enfocándose en el comportamiento de los médicos y/o farmacéuticos y todos ellos usan datos de preferencias reveladas para examinar el papel que juegan los expertos en el proceso por el que los pacientes reciben a bien un producto de marca o un genérico. Por el contrario, este trabajo, analiza directamente las preferencias de los consumidores por productos de marca o genéricos usando técnicas de preferencias declaradas basadas en una encuesta y modelos de elección discreta para la estimación. En particular , esta tesis analiza la demanda de medicamentos desde varias perspectivas. El primer capítulo explora, desde un punto de vista teórico, el impacto de los precios de referencia en la demanda de genéricos versus productos de marca y en las estrategias de precio de las empresas farmacéuticas. El segundo capítulo utiliza preferencias declaradas con el objetivo de estimar la importancia de la inducción de la profesinales sanitarios y de la fidelidad a la marca en el proceso de decisión entre medicamentos comerciales en una farmacia. Finalmente , el tercer capítulo procede a comparar empíricamente dos modelos de elección discreta que difieren en la escala de medida de la variable dependiente.
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Nosier, Shereen Adel Hassan. "Estimating the international tourism demand for Egypt : 'an econometric approach'." Thesis, University of Hull, 2012. http://hydra.hull.ac.uk/resources/hull:6861.
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The thesis aims to identify the main factors that significantly affect tourism demand for Egypt. Both time series data and panel data are used to model and forecast tourism demand for Egypt from all origins, as well as three individual regions of origin, including Europe, Arab and the Americas. The methodological and econometric approaches introduced in this thesis proceed from the simple to the more complex structure to obtain more reliable estimation. First, we estimate tourism demand for Egypt using the co-integration and error correction (CI/ECM) approach based on a single equation, followed by using a system of equations approach over the period 1970-2009. All the estimated econometric methods, in addition to two univariate time series methods, are used to generate ex-post forecasting for all the models over the period 2005-2009. The preferred method is used in producing ex-ante forecasting of future tourism demand for Egypt for the period 2010-2014. Panel co-integration techniques are also used to estimate tourism demand models over the period 1980-2009. Finally, the causality relationship between tourism demand and its economic determinants is estimated based on panel data analysis, which may provide more guidance for policy makers in Egypt. The results indicate that tourism demand for Egypt is found to be co-integrated with its fundamental determinants at the 1% significance level, with a high adjustment speed toward the steady state equilibrium. The importance of long-run income for all tourists from different nationalities is affirmed; with an elastic demand for non-Arab tourists. Price is also an important determinant, with a different effect in each originating region. It takes less than unity value for all tourists, except the Arab. Tunisia is found to be the most significant alternative to Egypt, with a complementary effect for Europe and the Americas tourists, but substitutability effect for Arab tourists. Hotel capacity is a significant and positive factor for all nationalities, except the Americas. Globalization is important in all models; it has a positive effect for all non-Arab nationalities. Political instability has a significant and negative effect, with the most effect on the Americas. All the determinants Granger cause tourist arrivals in the long run, but globalization and hotel capacity are of great importance with a bidirectional effect with tourist arrivals. Ex-post forecasting results show that the CI/ECMs outperform the other time series methods and produce highly accurate forecasts. The number of arrivals and nights from all origin markets is likely to increase in absolute terms (2010-2014), but with slower growth than recent trend.
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Stock, Curtis A. "Coast Guard Coastal Patrol Boat communications demand : an economic approach." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/26916.
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The Coast Guard is examining the requirements for a new Coastal Patrol Boat to replace the aging POINT class patrol boat. The communications capabilities of the new vessel class is of particular interest to its designers. The purpose of this thesis is to analyze the ship/shore data communications need as perceived by the operators. The theoretical framework of the study is based on economic theory and demand forecasting. Communications needs are estimated through a survey of operators both afloat and ashore with experience in the present POINT class patrol boat. Several implementation considerations are presented which, although not directly affecting the communications requirements, are important factors to the survey respondents. Three levels of service, or tiers, are then offered to meet the ship/shore communications needs identified in this study
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Mahamaneerat, Wannapa Kay Shyu Chi-Ren. "Domain-concept mining an efficient on-demand data mining approach /." Diss., Columbia, Mo. : University of Missouri--Columbia, 2008. http://hdl.handle.net/10355/7195.
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Title from PDF of title page (University of Missouri--Columbia, viewed on February 24, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. Chi-Ren Shyu. Vita. Includes bibliographical references.
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Breyer, Elizabeth Yancey. "Household Water Demand and Land Use Context: A Multilevel Approach." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1670.
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Urban water use arises from a mix of scale-dependent biophysical and socioeconomic factors. In Portland, Oregon, single-family residential water use exhibits a tightly coupled relationship with summertime weather, although this relationship varies with land use patterns across households and neighborhoods. This thesis developed a multilevel regression model to evaluate the relative importance of weather variability, parcel land use characteristics, and neighborhood geographic context in explaining single-family residential water demand patterns in the Portland metropolitan area. The model drew on a high-resolution panel dataset of weekly mean summer water use over five years (2001-2005) for a sample of 460 single-family households spanning an urban-to-suburban gradient. Water use was found to be most elastic with respect to parcel-scale building size. Building age was negatively related to water use at both the parcel and neighborhood scale. Half the variation in water use can be attributed to between-household factors. Between-neighborhood variation exerted a modest but statistically significant effect. The analysis decomposed household temperature sensitivity into four components: a fixed effect common to all households, a household-specific deviation from the fixed effect, a separate extreme heat effect, and a land use effect, where lot size exaggerated the effect of temperature on water use. Results suggested that land use planning may be an effective non-price mechanism for long-range management of peak demand, as land use decisions have water use implications. The combined effects of population growth, urbanization, and climate change expose water providers to risk of water stress. Modeling fine-grain relationships among heat, land use, and water use across scales plays a role in long-range climate change planning and adaptation.
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Bashagi, Asimwe. "An ARDL modelling approach to international tourism demand in Tanzania." Master's thesis, University of Cape Town, 2009. http://hdl.handle.net/11427/11874.
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Includes bibliographical references (leaves 39-42).<br>The objective of this study was to model the extent of international tourist demand in Tanzania. Thus, the study aimed to investigate the factors affecting international tourism demand. Domestic tourism prices, travel costs, alternative destination tourism prices, exchange rates, world income and taste formation were selected as the main determinants. Dummy variables for the September 2001 USA terror attack and the 1998 Tanzania US embassy bombing were also included in the model. The dummy variables were treated in two different ways, to capture the temporary and permanent effects these events had on tourism demand. The study applied the Autoregressive Distributed Lag approach to modelling international tourist demand in Tanzania. The findings are consistent with economic theory and with empirical evidence from other studies. The model passed all diagnostic tests. Therefore, the results from this study may be used as a guide in formulating relevant tourism policy for Tanzania.
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Ngai, Christopher. "Estimating the demand structure of housing characteristics: a nonparametric approach." Oberlin College Honors Theses / OhioLINK, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1342186655.
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LEE, TAI-CHUN. "AN EVENT-BASED APPROACH TO DEMAND-DRIVEN DYNAMIC RECONFIGURABLE COMPUTING." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin990821256.
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Ho, Xuyen, and not supplied. "Achieving a Sustainable Water Future for Ho Chi Minh City, Vietnam." RMIT University. Civil, Environmental and Chemical Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070518.124112.
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The current population in Ho Chi Minh City (HCMC) is more than 7 million. Due to pressures of increasing population, the developing economy and climate change, the future security of water supply is far from satisfactory. There is also pressure to connect a large number of customers currently not connected to the HCMC water supply reticulation grid. Current water resources management tends to be fragmented and focused purely on supply side management. It is not economically and environmentally sustainable to focus purely on augmenting supply to meet increasing demand. Sustainable water resources management requires a broader more holistic approach. Government's plans to improve current and future water management issues are examined in the context of two case studies, one from Australia (a developed country) and one from the Philippines (a developing country). The sustainable water management approaches adopted by these two case studies sit at either end of the s pectrum of options. One is closer to a centralized government planning model and the other is a more radical privatisation flavoured model. The thesis investigates the current water demand and supply balance for residential, commercial and industry; and propose a balanced strategy to meet the HCMC's demand until year 2020. The amount of water savings are calculated by implementing a suite of water conservation initiatives. The proposed initatives will substantially narrow the gap between the planned supply and forecasted demand, thus providing a acceptable reasonable supply security for the community.
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Dickson, Craig M. "Modeling Daily Power Demand in Southern Kentucky: A Single Household Approach." TopSCHOLAR®, 2012. http://digitalcommons.wku.edu/theses/1203.
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In this study, we use a nonparametric technique, locally weighted robust least squares regression (LOESS), to forecast a 24 hour demand profile at the household level and compare it to existing aggregate demand models discussed in literature. Of these aggregate demand models, a quadratic autoregressive model was selected to be used as a basis for comparison with the LOESS forecasts. It was our goal to automate the forecasting process by using the goodness of fit metric, AICCI, for smoothing parameter selection. The statistical workflow was executed using SAS and data was provided by the Glasgow Electric Plant Board of Barren County, Kentucky. Results show that LOESS outperformed the autoregressive model in roughly 80% of all cases and than using LOESS alone or as part of an ensemble model is a feasible approach to automating future household demand profile for the purpose of generating different levels of power demand profile aggregation as needed by Glasgow Electronic Plant Board.
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Guillaud, Elvire Gatti Donatella Amable Bruno. "Political economy of redistribution a comparative approach from the demand side /." Lyon : Université Lumière Lyon 2, 2008. http://theses.univ-lyon2.fr/sdx/theses/lyon2/2008/guillaud_e.
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Pattabhiraman, Varun R. (Varun Ramakrishna). "A needs-based approach to activity generation for travel demand analysis/." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/74470.
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Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 105-110).<br>This thesis develops a needs-based framework for behavioral enhancement of conventional activity-based travel demand models. Operational activity-based models specify activity generation models based on empirical considerations which are weakly founded in a behavioral theory. This thesis aims to enhance the specification of the activity generation models by developing the conceptual and analytical relationship between individuals' activity choices and need-satisfaction. The theory of needs hypothesizes that individuals conduct activities to satisfy their needs. Each activity that an individual conducts may satisfy one or several of their needs. Conversely, each need may be satisfied by one or several activities. This thesis models an individual's choice of activity dimensions including frequency, sequence, location, mode, time-of-travel, etc. as one that maximizes his/her need-satisfaction. A conceptual model of the relationship between needs and activities is developed based on inventory theory. Every need is associated with a psychological inventory that reflects the level of satisfaction with respect to the need. When an activity that satisfies a need is conducted, the need is satisfied and the corresponding psychological inventory is replenished by a quantity called the activity production. Over time, this inventory gets consumed and the need builds up. The choice of activity dimensions is modeled as a psychological inventory maximizing (i.e. utility-maximizing) problem, subject to time and cost budget constraints. The framework also accounts for satiation in need-satisfaction. An analytical model is formulated, solved and empirically estimated for a single need and the activity that satisfies the need under steady-state conditions. The problem is solved in two stages, for discrete (location) and continuous (duration and frequency) decision variables. The properties of the general solution are studied, and then explored for a translog form of the activity production function. An empirical estimation method that can be applied to single day travel diary data is proposed and validated using Monte-Carlo experiments. The model is empirically estimated using standard travel diary data from the Denver metropolitan area. Estimation results indicate the potential of the needs-based approach to enrich the specification of activity generation models in conventional activity-based model systems. A conceptual framework to extend the single need model is discussed. Extensions to models of multiple needs that capture interactions between different needs are also discussed. The flexible framework can also be extended to model social interactions including intrahousehold activity allocation and joint activity participation by households and social circles. An extension to a dynamic needs-based activity generation model is also discussed, which may be integrated with transportation simulators to predict individuals' activity choices in response to real-time information.<br>by Varun R. Pattabhiraman.<br>S.M.in Transportation
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Dave, Saraansh. "A systems approach to smart grids : demand side modelling and analysis." Thesis, University of Bristol, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658853.
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Information and communication technology has been identified as a key enabler to develop a resilient, low carbon, and secure future energy system, by creating a smart grid. Starting with the premise that technology can be used to effectively match demand to generation, we address three main questions; (i) can algorithms be used to coordinate demand? (ii) can policy influence market driven demand side solutions? and (iii) how does technology influence consumer behaviour? We find that demand management algorithms are sensitive to assumptions regarding consumer flexibility. Taking this into account, we develop a novel method to simultaneously evaluate demand response business cases within a regulatory context. We find that the value proposition for providing demand response services is weak and thus requires policy based incentives and support. The analysis of a smart home project indicates that in home display devices have a half-life of 17 weeks and this is not significantly affected by engagement campaigns. Participating in community led workshops (based on energy consumption) increases in home display device activity, however this is a very short term effect. We also find evidence that in home display devices are likely to be used after changes in energy consumption are made by the householder and not prior to behaviour change. When using the Theory of Planned Behaviour (TPB), energy saving groups (low, medium, and high) were found to have different values of subjective norm, perceived behaviour control, and intention. This is the first study to objectively measure behaviour change (in terms of energy saved and in home display usage) and compare it with self-reported values of the TPB within a smart home context.
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Miclo, Romain. "Challenging the "Demand Driven MRP" Promises : a Discrete Event Simulation Approach." Thesis, Ecole nationale des Mines d'Albi-Carmaux, 2016. http://www.theses.fr/2016EMAC0016/document.
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Les principaux enjeux des supply chain d’aujourd’hui concernent l’adaptation à des environnements instables. Demand Driven Material Requirements Planning (DDMRP) est une méthode récente et prometteuse de gestion des flux qui a été conçue pour faire face aux problématiques actuelles. Le travail de recherche réalisé détaille et positionne DDMRP par rapport aux autres méthodes connues de pilotage de flux. Le but de ce travail est de challenger les principales promesses de DDMRP. Pour cela, un plan d’expériences a été réalisé sur un cas d’étude pour évaluer le comportement de MRP II, Kanban et DDMRP face à différentes sources de variabilité. Le dimensionnement des buffers DDMRP est un sujet majeur pour la méthode. Il a été traité sur un cas d’étude avec un travail d’optimisation. Toutes les contributions ont été expérimentées avec l’implémentation de DDMRP sur un cas réel. La thèse permet ainsi de valider certains atouts de DDMRP, tels que l’adaptation du système à différentes formes de variabilités, mais elle permet également de souligner des perspectives majeures de recherche sur ce sujet<br>The main Supply Chain current issues concern the adaptation to unstable environments. Demand Driven Material Requirements Planning (DDMRP) is a recent and promising material management method that is designed to tackle these current issues. The research work details and classifies DDMRP compared to the other material management methods known. The goal of this work is to challenge the main DDMRP promises. This is why a design of experiments was realised on a case study in order to assess MRP II, Kanban and DDMRP behaviours with different variability sources. The DDMRP buffer sizing is a major issue. It was dealt with an optimisation work on a case study. All the contributions were experimented with a DDMRP implementation on a real case. The research work enables several DDMRP advantages to be validated, such as the system adjustment to different variability sources, however this work also allows research perspectives to be underlined
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Zhu, Xiaomei. "A Demand Driven Re-fleeting Approach for Aircraft Assignment Under Uncertainty." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/34814.
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The current airline practice is to assign aircraft capacity to scheduled
flights well in advance of departure. At such an early stage in this process,
the high uncertainty of demand poses a major impediment for airlines to best
match the airplane capacities with the final demand. However, the accuracy of
the demand forecast improves markedly over time, and revisions to the initial
fleet assignment become naturally pertinent when the observed demand
considerably differs from the assigned aircraft capacity. The Demand Driven
Re-fleeting (DDR) approach proposed in this thesis offers a dynamic
re-assignment of aircraft capacity to the flight network, as and when improved
demand forecasts become available, so as to maximize the total revenue.
Because of the need to preserve the initial crew schedule, this re-assignment
approach is limited within a single family of aircraft and to the flights
assigned to this particular family. This restriction significantly reduces the
problem size. As a result, it becomes computationally tractable to include
path level demand information into the DDR model, although the problem size
can then get very large because of the numerous combinations of composing
paths from legs. As an extension, models considering path-class level
differences, day-of-week demand variations, and re-capture effects are also
presented.
The DDR model for a single family with path level demand considerations is
formulated as a mixed-integer programming problem. The model's polyhedral
structure is studied to explore ways for tightening its representation and for
deriving certain classes of valid inequalities. Various approaches for
implementing such reformulation techniques are investigated and tested. The
best of these procedures for solving large-scale challenging instances of the
problem turns out to be an integrated approach that uses certain selected
model augmentations and valid inequalities generated via a suitable separation
routine and a partial convex hull construction process. Using this strategy in
concert with properly selected CPLEX options reduces the CPU time by an
average factor of 7.48 over an initial model for a test-bed of problems each
having 200 flights in total. Prompted by this integrated heuristic approach, a
procedure for finding solutions within a prescribed limit of optimality is
suggested. To demonstrate the effectiveness of these developed methodologies,
we also solved two large-scale practical-sized networks that respectively
involve 800 and 1060 flights, and 18196 and 33105 paths in total, with 300 and
396 flights belonging to the designated family. These problems were typically
solved within 6 hours on a SUN Ultra 1 Workstation having 260 MB RAM and a
clock-speed of 167 MHz, with one exception that required 14 hours of CPU time.
This level of computational effort is acceptable considering that such models
are solved at a planning stage in the decision process.<br>Master of Science
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Adams, Abigail. "The nonparametric approach to demand analysis : essays in revealed preference theory." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:d2a548aa-e720-4975-802b-e55d08dec9e6.
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This thesis comprises three principal essays, each of which provides a contribution to the literature on the nonparametric approach to demand analysis. In each essay, I develop novel techniques that follow in the revealed preference tradition, and apply them to tackle a series of questions that concern the mechanisms underlying consumer spending decisions. Each technique developed is tightly linked to a particular nonparametric theory of choice behaviour and is explicitly designed for use with a finite set of observations. My work draws heavily upon results from finite mathematics, into which I integrate insights from information theory and integer programming. The output of this endeavor is a set of methodologies that are largely free of auxiliary assumptions over the form of the unobserved structural functions of interest. Providing greater detail on the work to come, my first essay extends and clarifies the nonparametric approach to forecasting demand behaviour at new budget regimes. Using insights from information theory and integer programming, I construct an operational nonparametric definition of global rationality and develop a methodology that facilitates the recovery of globally rational individual demand predictions. This is the first attempt in the literature to develop a systematic methodology to impose global rationality on nonparametric demand predictions. The resulting forecasts allow for unrestricted preference heterogeneity in the population and I demonstrate how these predictions can be used for coherent welfare analysis. In my second and third essays, I prove new revealed preference testability axioms for models that extend the traditional neoclassical choice framework. Specifically, in my second essay, I address the intertemporal allocation of spending by collectives, whilst my final essay integrates taste variation into the utility maximisation framework. In both of these essays, I develop my testable results into practical algorithms that allow one to recover salient features of individual preferences. In my second essay, a methodology is developed to recover the minimal intrahousehold heterogeneity in theory-consistent discount rates, whilst my final essay develops a quadratic programming procedure that facilitates the recovery of the minimal interpersonal and intertemporal heterogeneity in tastes that is required to rationalise observed choice patterns. Applying these techniques to consumption micro-data yields new empirical insights that are of relevance to the applied literatures on time discounting, family economics and the public policy debate on tobacco control.
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Onuzo, Chika N. "An analysis of Georgia's energy demand ( a case study of gasoline and residential demand for electricity): a quantitative approach." DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 1985. http://digitalcommons.auctr.edu/dissertations/3262.
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This thesis analyzed Georgia's pre and post embargo consumption of gasoline and residential electricity from 1960 to 1982 to determine: 1) if the structure of gasoline demand was stable; 2) to investigate the arguments for conservation; and 3) to ascertain that the pricing mechanism is indeed able to adjust consumption to levels of supply. Elasticities were computed and they were used to address simple tax issues. The study was significant for several reasons: 1) it is the first ever known study of its kind done on Georgia; 2) Georgia has a ninety five percent dependence rate on other states and foreign countries (indirectly) for her supply of energy resources; 3) the impact of the oil embargo on consumption, prices and the economy at large is necessary both as a post moterm and for future policy decisions. The results overwhelmingly favored stability in the structure of these demands. As such, the restricted model was valid for any projections and conclusions. The short-term price and income elasticities for gasoline were .30 and .06 and the long-term coefficients were 1.5 and .20 respectively. For electricity, the short-term price and income elasticities were .22 and .37 and the long-term estimates were .81 and 1.33 respectively. The weather variables were very inelastic. All coefficients were significant by the usual criteria. With inelastic demands for these energy resources, taxation seemed a welcome proposition for controlling prices and consumption and for generating revenue. However, it is only to the extent that other monetary, fiscal and economic objectives of the government are not jeopardized. Thus, the arguments for conservation holds to a good degree. A hybrid of a comprehensive tax-pricing policy and conservation efforts is necessary for stability in the energy sector.
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Bijinemula, Sandeep Kumar. "An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/87403.
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Engine-triggered tasks are real-time tasks that are released when the crankshaft arrives at certain positions in its path of rotation. This makes the rate of release of these jobs a function of the crankshaft's angular speed and acceleration. In addition, several properties of the engine triggered tasks like the execution time and deadlines are dependent on the speed profile of the crankshaft. Such tasks are referred to as adaptive-variable rate (AVR) tasks. Existing methods to calculate the worst-case demand of AVR tasks are either inaccurate or computationally intractable. We propose a method to efficiently calculate the worst-case demand of AVR tasks by transforming the problem into a variant of the knapsack problem. We then propose a framework to systematically narrow down the search space associated with finding the worst-case demand of AVR tasks. Experimental results show that our approach is at least 10 times faster, with an average runtime improvement of 146 times for randomly generated task sets when compared to the state-of-the-art technique.<br>Master of Science<br>Real-time systems require temporal correctness along with accuracy. This notion of temporal correctness is achieved by specifying deadlines to each of the tasks. In order to ensure that all the deadlines are met, it is important to know the processor requirement, also known as demand, of a task over a given interval. For some tasks, the demand is not constant, instead it depends on several external factors. For such tasks, it becomes necessary to calculate the worst-case demand. Engine-triggered tasks are activated when the crankshaft in an engine is at certain points in its path of rotation. This makes their activation rate dependent on the angular speed and acceleration of the crankshaft. In addition, several properties of the engine triggered tasks like the execution time and deadlines are dependent on the speed profile of the crankshaft. Such tasks are referred to as adaptive-variable rate (AVR) tasks. Existing methods to calculate the worst-case demand of AVR tasks are either inaccurate or computationally intractable. We propose a method to efficiently calculate the worst-case demand of AVR tasks by transforming the problem into a variant of the knapsack problem. We then propose a framework to systematically narrow down the search space associated with finding the worst-case demand of AVR tasks. Experimental results show that our approach is at least 10 times faster, with an average runtime improvement of 146 times for randomly generated task sets when compared to the state-of-the-art technique.
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Havemann, Roy Charles. "The demand for labour in South Africa : a theoretical and empirical approach." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/50130.
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Thesis (MComm)--Stellenbosch University, 2004.<br>ENGLISH ABSTRACT: Nearly five million South Africans were unemployed in 2002 and creating
employment opportunities is a difficult challenge. Before this issue can be tackled,
however, it is critical to understand the problem. This thesis opts to contribute to this
understanding by considering aspects around the demand for labour. The analysis
considers a selection of the theoretical literature on the demand for labour, estimates
key labour market parameters and then undertakes a number of simulations using a
structural model.
There are many conflicting paradigms that can be used to analyse the issue:
microeconomic versus macroeconomic; neoclassical versus structuralist; theoretical
versus empirical and so forth. Some of these paradigms are considered as part of the
attempt to build an empirical framework that can be used to analyse the issue.
The empirical results of the thesis suggest that:
• Higher real wages lead to lowering of the quantity demanded of labour. The
thesis estimates an economy-wide wage elasticity of employment of
approximately -0,67;
• Higher output stimulates the demand for labour. The single equation estimate
of the employment elasticity of output is between 0,66 and 0,75, whilst the
economy-wide estimate is approximately 1,1. The latter takes into account
feedback effects from other macroeconomic variables, such as productivity
and wages;
• There is little evidence to show that the efficiency wage hypothesis holds -
higher productivity leads to higher wages, but the converse is not true;
• Union power increases real wages, indirectly leading to a fall in the demand
for labour. This suggests that the labour market has insiders and outsiders; and
• The relative price of labour is also important, with a fall in the cost of capital
leading to a decrease in the demand for labour.
Simulations suggest that job creation can be achieved through policies that encourage
wage moderation and increase economic growth. There is also a potential role, albeit
limited, for fiscal incentives such as a mooted earned income tax credit.<br>AFRIKAANSE OPSOMMING: Byna vyf miljoen Suid-Afrikaners was werkloos in 2002 en werkskepping is 'n
moeilike uitdaging. Voordat hierdie kwessie aangepak kan word, is dit egter
noodsaaklik om die probleem te verstaan. Hierdie tesis dra by tot hierdie begrip deur
te fokus op punte rondom die vraag na arbeid. Die ontleding kyk na 'n verskeidenheid
van teoretiese literatuur oor die vraag na arbeid en identifiseer sleutel-parameters vir
die arbeidsmark.
Daar is soveel teenstrydige paradigmas wat gebruik kan word om die kwessie te
ontleed: Mikro-ekonomies teenoor makro-ekonomies; neoklassiek teenoor
strukturalisties; teoreties teenoor empiries, ensovoorts. Sommige van hierdie
paradigmas word bespreek as deel van die poging om 'n empiriese raamwerk te bou
wat gebruik kan word om die kwessie te ontleed.
Die empiriese resultate van die tesis toon:
• Hoër reële lone lei tot 'n verlaging van die hoeveelheid arbeid aangevra. Die
tesis beraam die ekonomiewye loonelastisiteit van indiensneming op sowat -
0,67;
• Hoër uitset stimuleer die vraag na arbeid. Die enkelvergelyking-raming van
die uitset-elastisiteit van indiensneming is tussen 0,66 en 0,75, terwyl die
ekonomiewye raming sowat 1,1 is. Laasgenoemde neem terugvoerinvloede
van ander makro-ekonomiese veranderlikes in ag, bv. produktiwiteit en lone.
• Daar is min bewyse dat die doeltreffende loon-hipotese water hou: Hoër
produktiwiteit lei tot hoër lone, maar die teendeel is onwaar;
• Vakbonde se mag verhoog reële lone, wat indirek lei tot 'n daling van die
vraag na arbeid. Dit dui daarop dat die arbeidsmark 'n binnekring en
buitestaanders het; en
• Die relatiewe prys van arbeid is ook belangrik: 'n Afname van die koste van
kapitaal veroorsaak 'n daling van die vraag na arbeid.
Simulasies toon dat werkskepping bevorder kan word deur beleid wat loonmatiging
en ekonomiese groei bevorder. Daar is ook 'n rol, alhoewel beperk, vir fiskale
insentiewe, b.v. 'n loonsubsidie.
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Mougeot, Sylvie R. (Sylvie Renee) Carleton University Dissertation Management Studies. "Demand for Canadian bank notes by denomination; a combined share/ regression approach." Ottawa, 1997.
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Cao, Z. "Modelling economic interdependencies of international tourism demand : the global vector autoregressive approach." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/810483/.
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Tourism demand is one of the major areas of tourism economics research. The current research studies the interdependencies of international tourism demand across 24 major countries around the world. To this end, it proposes to develop a tourism demand model using an innovative approach, called the global vector autoregressive (GVAR) model. While existing tourism demand models are successful in measuring the causal effects of economic variables on tourism demand for a single origin-destination pair, they tend to miss the spillover effects onto other countries. In the era of globalisation, tourism destinations become interdependent on each other. Impacts of a distant event can be transmitted across borders and be felt globally. Hence, modelling international tourism demand requires one to go beyond a particular origin-destination pair, and take into account the interdependencies across multiple countries. The proposed approach overcomes the ‘curse of dimensionality’ when modelling a large set of endogenous variables. The empirical results show that, to different extents, co-movements of international tourism demand and of macroeconomic variables are observed across all the 24 countries. In the event of a negative shock to China’s real income level and that to China’s own price level, it is found that in the short run, almost all countries will face fluctuations in their international tourism demand and their own price. But in the long run the shocks will impact on developing countries and China’s neighbouring countries more deeply than on developed countries in the West. The current research contributes to the knowledge on tourism demand. It models tourism demand in the setting of globalisation and quantifies the interdependencies across major countries. On the practical front, tourism policy makers and business practitioners can make use of the model and the results to gauge the scale of impacts of unexpected events on the international tourism demand of their native markets.
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Goh, Bee Hua. "Construction demand modelling : a systematic approach to using economic indicators and a comparative study of alternative forecasting approaches." Thesis, University College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.393033.
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Shang, Feng. "Path-dependent approach to estimate chlorine wall demand coeffcient in water distribution system." Cincinnati, Ohio : University of Cincinnati, 2005. http://www.ohiolink.edu/etd/view.cgi?acc%5Fnum=ucin1109274766.
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Zajicek, Edward K. "Valuation of quality determinants in consumer demand for automobile : a hedonic price approach /." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-08232007-112211/.
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Al-Noaimi, Mubarak Aman. "Development of water resources in Bahrain : a combined approach of supply-demand analysis." Thesis, University of Plymouth, 2004. http://hdl.handle.net/10026.1/1951.
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Bahrain is an arid country with acute water shortage problems. The demand for water has increased substantially over the last four decades, leading to over-exploitation from the already scarce renewable groundwater resources. This has caused a significant decline in groundwater levels, a drastic storage depletion, and serious deterioration in groundwater quality. The imbalance between the available water supply and the projected water demand has been growing rapidly, imposing a major constraint on the country's socio-economic development. Resolving these problems or at least mitigating their adverse impacts primarily requires a major shift from the supply-oriented approach to water planning, which is currently being emphasised, towards a greater emphasis on demand-side management policies. In this thesis, a combined approach of supply-demand analysis is employed to investigate the water and management problems in the study area, with the ultimate objective of establishing a supply-demand analytical framework to aid in the formulation of an integrated water management policy. The existing water resources are comprehensively assessed in terms of availability and development constraints. The water use patterns and demand characteristics are systematically analysed. The results of these analyses are shown to have important implications from the water resources planning and management perspective. Using data from cross-sectional surveys, separate water demand functions of both linear and log-linear functional forms are estimated for the major water use activities. The empirical evidence presented in this research suggests that certain socio-economic, demographic, physical, climatic, and technological factors affect water use. The variables household size and household/per capita income are found to be the most important determinants of residential water use, with a priori expected signs. Average price, however, does not have a statistically significant effect. Estimated income elasticities vary from 0.12 to 0.22; household size elasticities range from 0.30 to 0.41. Empirical estimates for summer and winter residential demand functions suggest some interesting findings with respect to the seasonal variability in water use. Per capita income elasticities of municipal demand of between 0.15 - 0.33 are estimated. Both the residential and municipal income elasticity estimates appear to correlate favourably with some estimates found in the literature. Not surprisingly, average price elasticity of per capita municipal demand is estimated to be -0.066, indicating an extremely inelastic demand. In general, the empirical findings from both the non-residential and agricultural surveys give less reliable statistical results, perhaps owing to the insufficiency of data and/or lack of specific explanatory variables. However, the variables number of bathrooms and presence of swimming pool may be adequate indicators of the non-residential water use, while gross cultivated area appears to be the best single predictor of the agricultural water use. Industrial water demand is shown to be significantly and directly related to the variables measuring production level, number of employees, and factory floor area. Validity tests for the selected analytical models are made. The water supply and demand relationships are examined and water balances for the specified planning period are computed. The improved trend forecasting procedures provide encouragingly accurate results when compared to the actual water use. Three alternative water management scenarios are developed. Comparison among these scenarios indicates that Scenario C, which integrates the supply and demand management policies, is the most efficient option for achieving optimal water resources development and management. Policy recommendations to enable effective formulation and implementation of this option are presented.
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Ali, Mir Shabbar. "An accessibility-activity based approach for modelling rural travel demand in developing countries." Thesis, University of Birmingham, 2001. http://etheses.bham.ac.uk//id/eprint/900/.
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For most rural populations in developing countries, travel to access basic needs is considered a burden, in terms of wastage of their daily time and efforts. Lack of adequate access to health, education and market centres is found to be responsible for problems like high mortality rate and low literacy rate and high sense of isolation. Recent research has recommended that time constraints should be incorporated in attempting to model rural travel behaviour. The research reported in this thesis integrates household accessibility analysis within an activity-based framework to model travel demand. The conceptual development recognised the derived nature of travel. The household access needs are transformed into individual activities through household role allocation. The spatial and temporal constraints on the activities along with monetary, cultural and social constraints on individuals determine accessibility of the activities to the individuals. Probabilistic behavioural models have been developed to model individual activity choice and the resulting travel. Household data collected from representative rural areas of Pakistan were used to analyse rural activity-travel behaviour. Household activities analysed were Work, Education, Market, Health and Leisure. The results indicated the varying nature of these activities and that of individuals responsible for carrying out the activities. It was found that Household Heads are responsible for carrying out most out-of-home activities required to fulfil household needs. Models developed were applied to various situations. The models in general were found to validate the concepts developed in the research. Prediction results for activities Work and Education were in agreement to the observed data. Results for activities Market, Health and Leisure showed that a time horizon must be considered to recognise the nondaily nature of these activities. Models addressing time horizon decision showed better agreement between predicted and observed travel demand.
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Hamilton, I. G. "Energy epidemiology : an epidemiological approach to empirically-based population-level energy demand research." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1469031/.
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The shift to a low carbon economy and the need to address energy demand priorities will involve the retrofit of millions of buildings resulting in changes in energy demand services at the national and international scale. Studying energy demand in buildings at a population level is different than in individual or small samples because of population heterogeneity. Evaluating policies and determining the effect of technologies in situ in millions of buildings means using techniques that support that level of analysis and use empirically derived data that can represent complex real-world conditions. Health epidemiology, which studies the distribution and determinants of population health outcomes, offers a compelling framework for studying population level energy demand. The aim of this thesis is to determine whether the adaption of the conceptual and methodological framework of epidemiology can support the study of energy, people and buildings. This thesis tests this hypothesis by examining relevant epidemiological concepts and its methodological framework along with three studies that adapt and apply epidemiological methods to energy demand and energy efficiency retrofits in UK houses. The method studies use a database of over 13 million dwellings to study energy efficiency retrofit uptake and their impact on energy demand. The method study findings support the case that an epidemiological approach to energy demand provides an appropriate and plausible conceptual and methodological framework for determining population-level evidence to inform modelling and policy development and evaluation. Adapting the epidemiological approach is not a panacea to dealing with the challenges facing the field of research in energy demand in buildings. However, it does provide a set of concepts, methods and analysis tools that are capable of supporting an empirically-based population-level research approach, identified as a necessary step towards to developing a robust foundation of evidence.
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Dostálová, Kristýna. "On the demand and supply of local public goods : a quasi-experimental approach." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1G003.
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L'objectif de cette thèse de doctorat est d'étudier l'adéquation entre l'offre de biens publics locaux et la demande des citoyens. D'un point de vue théorique, les modèles analysant la demande de service public, tel le modèle de l'électeur médian ou l'hypothèse de Meltzer et Richard, démontrent que les caractéristiques de l'électorat ainsi que ses préférences sont les principaux déterminants des choix publics. Les modèles analysant l'offre de service public concluent au contraire que c'est la composition du gouvernement (nombre de partis, idéologie des élus) qui joue un rôle décisif. Cette recherche a pour objet de faire le lien entre ces deux catégories d'explications, à travers une série d'essais empiriques utilisant une approche quasi-expérimentale, et se basant sur une analyse du secteur public local français et finlandais.L'analyse des dépenses de fonctionnement des départements français montre que les gouvernements ayant une majorité de sièges à gauche ne dépensent pas plus en aide sociale que leurs homologues à droite. Les niveaux de dépense dépendent au contraire du nombre d'usagers et de leur répartition entre les quatre risques que sont le chômage, l'aide à la famille, l'aide aux personnes handicapées et aux personnes âgées. Sur données finlandaises, l'approche quasi-expérimentale montre en moyenne qu'il n'y a pas de différence significative entre les dépenses des gouvernements majoritaires et celles des gouvernements minoritaires. La demande des citoyens semble donc jouer un rôle prédominant dans l'explication des niveaux de dépenses publiques locales pour ces deux pays<br>The aim of the PhD thesis is to study the demand and supply sides of local public good provision. Demand driven models, such as the median voter theorem or the Meltzer and Richard hypothesis, state that the characteristics and preferences of the electorate are the main forces driving public decisions. Models focusing on the supply side argue instead that the composition of governing bodies (e.g., number of parties, ideology of elected officials) is the key explanatory factor. The thesis seeks to shed light on the connection between the two categories of explanations, through a series of empirical essays, using a quasi-experimental approach to study the local public sector in France and Finland.The analysis of operating expenditures of the French Departments shows that left-wing governments do not spend more on social assistance than their right-wing counterparts. Spending levels depend instead on the number of welfare recipients and their type: children, unemployed, disabled and elderly people. For Finnish municipalities, the quasi-experimental approach indicates that there is no significant difference between the expenditures of majority governments and those of minority governments. The demand side, i.e., the electorate, thus seems to play an important role in explaining policy choices in the two countries
37
Mattson, Jeremy. "Innovative Approach to Estimating Demand for Intercity Bus Services in a Rural Environment." Diss., North Dakota State University, 2017. http://hdl.handle.net/10365/25945.
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Because existing models have their limitations, there is a significant need for a model to estimate demand for intercity bus services, especially in rural areas. The general objective of this research was to develop an intercity mode choice model that can be incorporated into a statewide travel demand model to estimate demand for rural intercity bus services. Four intercity transportation modes were considered in the study: automobile, bus, rail, and air. A stated preference survey was conducted of individuals across the state of North Dakota, and a mixed logit model was developed to estimate a mode choice model. Results from the mode choice model showed the significant impacts of individual, trip, and mode characteristics on choice of mode. Gender, age, income, disability, trip purpose, party size, travel time, travel cost, and access distance were all found to have significant impacts on mode choice, and traveler attitudes were also found to be important. The study demonstrated how the mode choice model can be incorporated into a statewide travel demand model, and intercity bus mode shares were estimated for origin-destination pairs within the state. Alternative scenarios were analyzed to show how mode shares would change under different conditions or service characteristics. This study was conducted in the largely rural state of North Dakota, but results could be transferable to other areas with similar geographic characteristics.<br>U.S. Department of Transportation (USDOT)
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Teo, William W. J. "A natural language processing approach to improve demand forecasting in long supply chains." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127104.
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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, May, 2020<br>Cataloged from the official PDF of thesis.<br>Includes bibliographical references (pages 74-80).<br>Information sharing is one of the established approaches to improve demand forecasting and reduce the bullwhip effect, but it is infeasible to do so effectively in a long supply chain. Using the polystyrene industry as a case study, this thesis explores the usage of modern natural language processing (NLP) techniques in a deep learning model, known as NEMO, to forecast the demand of a commodity -- without requiring downstream companies to share information. In addition, this thesis compares the effectiveness of such an approach with other non-deep learning approaches, specifically an ARIMA model and a gradient boosting model, XGBoost, to demand forecasting. All three models returned large forecast errors. However, NEMO tracked the volatility of actual data better than the ARIMA model. NEMO also had better success in predicting demand than the XGBoost model, returning approximately 20% better Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) scores. This result suggests that NEMO can be improved with better data, but other issues, such as legality of text mining, need to be considered and addressed before NEMO can be used in day-to-day operations. In its current form, NEMO can be used alongside other forecasting models and provide invaluable information about upcoming demand volatility.<br>by William W.J. Teo.<br>M. Eng. in Supply Chain Management<br>M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program
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Subbiah, Rajesh. "An activity-based energy demand modeling framework for buildings: A bottom-up approach." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23084.
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Energy consumption by buildings, due to various factors such as temperature regulation, lighting, poses a threat to our environment and energy resources. In the United States, statistics reveal that commercial and residential buildings combined contribute about 40 percent of the overall energy consumption, and this figure is expected to increase. In order to manage the growing demand for energy, there is a need for energy system optimization, which would require a realistic, high-resolution energy-demand model. In this work, we investigate and model the energy consumption of buildings by taking into account physical, structural, economic, and social factors that influence energy use. We propose a novel activity based modeling framework that generates an energy demand profile on a regular basis for a given nominal day. We use this information to generate a building-level energy demand profile at highly dis-aggregated level. We then investigate the different possible uses of generated demand profiles in different What-if scenarios like urban-area planning, demand-side management, demand sensitive pricing, etc. We also provide a novel way to resolve correlational and consistency problems in the generation of individual-level and building-level "shared" activities which occur due to individuals\' interactions.<br>Master of Science
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De, Villiers Dylan. "A modern econometric approach to estimating theoretically consistent demand systems of retail brands." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/10360.
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This paper conducts an empirical investigation of the cake mix and frosting demand system using daily data on sales figures, prices and marketing mix variables. SUR maximum likelihood is used to estimate static and dynamic (error correction) linear almost ideal demand systems. Results compare static and dynamic model estimates.
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SHANG, FENG. "PATH-DEPENDENT APPROACH TO ESTIMATE CHLORINE WALL DEMAND COEFFICIENT IN WATER DISTRIBUTION SYSTEM." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1109274766.
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Storry, Rachael Louise. "A multi-objective optimisation approach to the network arrangement of flexible heat demand." Thesis, University of Strathclyde, 2014. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=24394.
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The electricity network in the UK is facing a challenging future where environmental and efficiency goals to be met require significant changes in the industry. The rethinking of how distribution networks are arranged and operated is essential due to increasing connections of generation at this level. This also gives significance to the issue of arranging and operating these assets in the most optimal manner. The saturated state of the transmission network has led to the popularity of connecting generation to distribution networks. It becomes evident that, when increasing generation from renewable sources, a means of storing energy is required. One area of storage being investigated for this aim is Electrical Thermal Storage (ETS), which is a form of flexible heating demand. This type of energy storage is cost effective, however it is limited in its application due to the natural dissipation of heat. It is preferable that this heat loss be of use and therefore ETS devices are used in the domestic setting. These devices can be in the form of space storage heaters or hot water storage tanks, which are able to store heat or hot water for up to several days, until the user wishes to make use of the resource. Although decentralised generation and energy storage (Distributed Energy Resources - DER) at first glance appear to be an attractive means for the energy and carbon targets to be met, it can introduce further problems to the electricity network. It is possible for the addition of DER to lead to voltage rise or voltage drop, negatively impact on the protection systems and affect power quality. In order for distribution networks to successfully operate it is important that any new network assets are connected in an optimal manner. This research has modified and used a multi-objective network planning framework to determine the optimal arrangement of ETS devices in distribution networks. The framework is built around the Strength Pareto Evolutionary Algorithm 2 (SPE A2), which takes its inspiration from evolution in nature, and is able to take into consideration the constraints of the network and multiple, conflicting objectives. The framework has been adapted to optimise the number of ETS devices, their location and operation, whilst ensuring that the network will operate within its constraints. The results generated by the planning framework illustrate the potential benefits offered by the inclusion of ETS in distribution networks, as well as demonstrate that the method and tools used are valuable and appropriate.
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Taylor, Lance, Armon Rezai, and Duncan K. Foley. "An Integrated Approach to Climate Change, Income Distribution, Employment, and Economic Growth*." WU Vienna University of Economics and Business, 2015. http://epub.wu.ac.at/4557/1/EcolEcon_WorkingPaper_2015_3.pdf.
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A demand-driven growth model involving capital accumulation and the dynamics of
greenhouse gas (GHG) concentration is set up to examine macroeconomic issues raised by global
warming, e.g. effects on output and employment of rising levels of GHG; offsets by mitigation;
relationships among energy use and labor productivity, income distribution, and growth; the
economic significance of the Jevons and other paradoxes; sustainable consumption and possible
reductions in employment; and sources of instability and cyclicality implicit in the twodimensional
dynamical system. The emphasis is on the combination of biophysical limits and Post-
Keynesian growth theory and the qualitative patterns of system adjustment and the dynamics that
emerge.<br>Series: Ecological Economic Papers
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Kagiri, Charles Muiruri. "Optimal approach to energy management and gas delivery of a compressed natural gas station." Thesis, University of Pretoria, 2019. http://hdl.handle.net/2263/77831.
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The global growth in demand for transportation has been phenomenal, owing to an exponential
increase in population, industrialization and urbanization. This has led to a corresponding increase in
the number of motor vehicles on the roads globally which has made the transport industry one of the
main contributors to environmental pollution and energy insecurity. The profile of alternative fuels
has been rising as an important component of the solutions to the challenge of energy sustainability.
Compressed natural gas is one of the most successful alternative fuels for motor vehicle applications
because of its compatibility with the internal combustion engine, reduced engine maintenance costs,
reduced criteria air pollutants, low cost, abundance and the existence of renewable sourced natural gas
from biomass. The infrastructure for the delivery of compressed natural gas forms part of the primary
energy supply network, which has a significant interdependence with the electricity supply network.
The compressed natural gas fuelling station is one of the vital nodes of the gas delivery network, that
is also reliant on the electricity supply due to the energy intensive compressors that are required to
achieve the right pressure conditions for gas transfer to vehicle tanks.
At the same time, the increase in human population, industrialization, urbanization and market volatility
have threatened the reliability and stability of electricity supply networks. Traditional reliance on
supply upgrading to meet rising demand has proven to be unsustainable due to prohibitively high costs
and associated environmental impact. As a result, demand side management solutions, where better use
of the existing capacity is emphasized have received increasing attention. Demand side management
requires that electricity consumers also play a role in the efficient operation of the electricity grid by
minimizing their electricity usage as well as shifting their flexible loads away from peak electricity
demand periods, so that grid stability is sustained.
In order to participate in demand side management initiatives, operators of compressed natural gas
stations need technically and economically sound strategies for the operation of station compressors
and system components so that energy costs are minimized and gas transfer performance is enhanced.
The compressed natural gas fast-fill station, being the most used configuration for commercial fuelling
service is the focus of the work carried out in this thesis, with a description of solutions to minimize
energy consumption, minimize energy costs and improve gas transfer performance through reduction
of filling time.
For this purpose, firstly, an optimal control strategy that minimizes energy cost by shifting the compressor
load optimally away from the peak electricity pricing period under a time-of-use electricity
tariff, while meeting the gas demand is modelled and evaluated. The controller further minimizes the
switching frequency of the compressor thereby avoiding an increase in wear and tear which would
lead to higher maintenance costs. The results show the effectiveness of the optimal operation model to
achieve a huge reduction in electricity cost for the compressed natural gas station, when compressor-on
time is shifted to offpeak and standard electricity pricing times. Further strategies for the minimization
of switching frequency are compared and the superior approach identified.
Secondly, a hierarchical operation optimization model is designed and evaluated. The strategy achieves
minimized electricity cost and optimal vehicle filling time by optimally controlling the gas dispenser
and priority panel valve function under an optimised schedule of compressor operation. The results
show that the proposed approach is effective in achieving a minimum electricity costs in the upper
layer optimisation while meeting vehicle gas demand over the control horizon. Further, a reduction in
filling time is achieved through a lower layer model predictive control of the pressure-ratio-dependent
fuelling process.
Thirdly, an evaluation of compressor optimal sizing is carried out to minimize energy consumption
and cascade the benefits of optimal operation of the compressed natural gas compressor under the
time-of-use tariff. A comparison of the implication of using a variable speed drive or a fixed speed
drive which are optimally sized is carried out. Results show that indeed further reduction in electricity
costs for the compressed natural gas station is realized when optimally sized compressor drives are
used in combination with optimal operation strategies. Additionally, the four line priority panel is
evaluated for gas transfer performance and found to further increase the efficiency of vehicle fuelling
which is a performance indicator for consumer convenience.
The outcomes of this work demonstrate the effectiveness of the approaches proposed as necessary
to integrate compressed natural gas stations, which are vital nodes of the gas delivery network,
with the demand side management of the electricity grid while at the same time enhancing the gas
transfer performance. This increases the economic efficiency of the compressed natural gas as an
alternative fuel and also advances the goals of demand side management in electricity grid reliability
and stability.<br>Thesis (PhD)--University of Pretoria, 2019.<br>Electrical, Electronic and Computer Engineering<br>PhD<br>Unrestricted
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Bian, Desong. "An Expert-based Approach for Demand Curtailment Allocation Subject to Communications and Cyber Security Limitations." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/74930.
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A smart grid is different from a traditional power system in that it allows incorporation of intelligent features and functions, e.g., meter reading, adaptive demand response, integration of distributed energy sources, substation automation, etc. All these intelligent features and functions are achieved by choosing appropriate communication technologies and network structures for the smart grid appropriately.
The objective of this dissertation is to develop an AHP (analytic hierarchy process) - based strategy for demand curtailment allocation that is subject to communications and cyber security limitations. Specifically, it: (1) proposes an electrical demand curtailment allocation strategy to keep the balance between supply and demand in case of the sudden supply shortage; (2) simulates the operation of the proposed demand curtailment allocation strategy considering the impact from communication network limitations and simultaneous operations of multiple smart grid applications sharing the same communication network; and (3) analyzes the performance of the proposed demand curtailment allocation strategy when selected cyber security technologies are implemented. These are explained in more details below.
An AHP-based approach to electrical demand curtailment allocation management is proposed, which determines load reduction amounts at various segments of the network to maintain the balance between generation and demand. Appropriate communication technologies and the network topology are used to implement these load reduction amounts down to the end-user. In this proposed strategy, demand curtailment allocation is quantified taking into account the demand response potential and the load curtailment priority of each distribution substation. The proposed strategy helps allocate demand curtailment (MW) among distribution substations or feeders in an electric utility service area based on requirements of the central load dispatch center.
To determine how rapidly the proposed demand curtailment strategy can be implemented, the capability of the communication network supporting the demand curtailment implementation needs to be evaluated. To evaluate the capability of different communication technologies, selected communication technologies are compared in terms of their latency, throughput, reliability, power consumption and implementation costs. Since a number of smart grid applications share the same communication network, the performance of this communication network is also evaluated considering simultaneous operation of popular smart grid applications.
Lastly, limitations of using several cyber security technologies based on different encryption methods - 3EDS (Triple Data Encryption Standard), AES (Advanced Encryption Standard), Blowfish, etc. - in deploying the proposed demand curtailment allocation strategy are analyzed.<br>Ph. D.
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Goddard, Timothy Glenn. "A systematic approach to the design of weaving preparation systems operating under variable demand." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/8526.
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Wong, Ho-ting, and 黃浩霆. "Biometeorological modelling and forecasting of ambulance demand for Hong Kong: a spatio-temporal approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B4775297X.
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The demand for emergency ambulance services in Hong Kong is on the rise.
Issues such as climate change, ageing population, constrained space, and limited
resource capacity mean that the present way of meeting service demand by injecting
more resources will reach its limit in the near future and unlikely to be sustainable.
There is an urgent need to develop a more realistic forecast model to account for the
anticipated demand for emergency ambulance services to enable better strategic
planning of resources and more effective logistic arrangement. In this connection, the
research objectives of this thesis include the following:
1. To examine relationships between weather and ambulance demand, with
specific reference to temperature effects on demographic and admission
characteristics of patients.
2. To establish a quantitative model for short-term (1-7 days ahead) forecast of
ambulance demand in Hong Kong.
3. To estimate the longer-term demand for ambulance services by sub areas in
Hong Kong, taking into account projected weather and population changes in 2019 and 2036.
The research concurs with the findings of other researchers that temperature was
the most important weather factor affecting the daily ambulance demand in
2006-2009, accounting for 49% of the demand variance. An even higher demand
variance of 74% could be explained among people aged 65 and above. The
incorporation of 1-7 day forecast data of the average temperature improved the
forecast accuracy of daily ambulance demand on average by 33% in terms of R2 and
11% in terms of root mean square error (RMSE). Moreover, the forecast accuracy
could be further improved by as much as 4% for both R2 and RMSE through spatial
sub models. For demand projection of a longer-term, significant underestimation was
observed if changes in the population demographics were not considered. The
underestimation of annual ambulance demand for 2019 and 2036 was 16% and 38%
respectively.
The research has practical and methodological implications. First, the
quantitative model for short-term forecast can inform demand in the next few days to
enable logistic deployment of ambulance services beforehand, which, in turn, ensures
that potential victims can be served in a swift and efficient manner. Second, the
longer-term projection on the demand for ambulance services enables better
preparation and planning for the expected rise in demand in time and space.
Unbudgeted or unnecessary purchases of ambulances can be prevented without
compromising preparedness and service quality. Third, the methodology is adaptable
and the model can be reconstituted when more accurate projections on weather and
population changes become available.<br>published_or_final_version<br>Geography<br>Doctoral<br>Doctor of Philosophy
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Ebina, Takeshi, and Takanori Adachi. "Log-Linear Demand Systems with Differentiated Products Are Inconsistent with the Representative Consumer Approach." 名古屋大学大学院経済学研究科附属国際経済政策研究センター, 2014. http://hdl.handle.net/2237/21071.
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Kim, Seok-Chool. "Forecasting international demand for tourism to South Korea : a cointegration and error correction approach." Thesis, University of Surrey, 1997. http://epubs.surrey.ac.uk/2173/.
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Ho, To Ming. "Export supply and import demand functions of Hong Kong : a dual production theory approach." Thesis, University of Southampton, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239404.
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