Bibliografías temáticas / Global demand

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Literatura académica sobre el tema "Global demand"

Autor: Grafiati

Publicado: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Global demand"

Gadzalo, Iaroslav, Mykola Sychevskiy, Olha Kovalenko, Liudmyla Deineko y Lyudmila Yashchenko. "Assessment of global food demand in unexpected situations". Innovative Marketing 16, n.º 4 (18 de diciembre de 2020): 91–103. http://dx.doi.org/10.21511/im.16(4).2020.08.

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The methodological approach for assessing the formation of food demand in unforeseen situations using digital Internet-technologies and the assessment itself, is substantiated in the paper (in the context of the COVID-19 pandemic of 2020). Comparison and theoretical generalization, as well as statistical test-assessment of hypotheses and structural regularities based on the data of Google Trends Internet platform, is used to analyze consumer preferences and intensity of demand changes for meat, milk, sugar, bread, and flour during the pandemic and quarantine, both in developed and developing countries. It is discovered that the biggest changes can be observed in the developed countries: consumer preferences shifted from rather expensive food products (milk and meat) to much cheaper ones (flour and bread). It is asserted that a decrease in consumer demand for basic food products will have a negative impact on the global economy. In 2020, a considerable decrease in GDP is expected for the developed countries; in the developing countries, GDP decline will not be as large, but prices are expected to rise much more noticeably. The following anti-crisis measures are proposed: support of the most vulnerable population and increase of food accessibility; temporary reduction of the VAT and other taxes influencing the price of food; reduction of central banks’ lending rates, etc. With the correct measures applied, the stabilization of consumer demand for food and gradual growth of the global economy is expected by the end of 2021.

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Donnelly, John. "Comments: Global Demand Surge". Journal of Petroleum Technology 63, n.º 08 (1 de agosto de 2011): 14. http://dx.doi.org/10.2118/0811-0014-jpt.

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Omori, Natsuki. "Global Woodchips Supply/Demand". JAPAN TAPPI JOURNAL 73, n.º 8 (2019): 705–8. http://dx.doi.org/10.2524/jtappij.73.705.

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Gehlert, Kurt M., Thomas Ressler y Donoxti Baylon. "Global challenges demand global education of systems thinking". Human Systems Management 32, n.º 2 (2013): 79–94. http://dx.doi.org/10.3233/hsm-120777.

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Robert, Patrick. "Global plasma demand in 2015". Pharmaceuticals, Policy and Law 11, n.º 4 (2009): 359–67. http://dx.doi.org/10.3233/ppl-2009-0250.

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Shirai, Sayuri y Eric Alexander Sugandi. "Growing Global Demand for Cash". International Business Research 12, n.º 12 (25 de noviembre de 2019): 74. http://dx.doi.org/10.5539/ibr.v12n12p74.

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Demand for cash is generally known to be influenced by several factors—including transaction motive used for payment, opportunity cost, precautionary motive, and other motives (such as aging and demand from abroad). In recent years, cashless payment methods have increasingly become prevalent in the world through various conventional tools and innovative convenient financial services using mobile phones and smart phones. Nevertheless, cash in circulation has been rising in many economies, especially after the global financial crisis. This paper seeks to examine factors affecting cash in circulation for 22 economies for the period 2000–2018. It also investigated the movements of banknotes in circulation differentiated by denomination for seven economies whose data were available. The empirical analysis of this paper found that the opportunity cost proxied by the central bank policy rates and age-related variable were the two most important robust determinants for cash demand. Namely, cash demand tends to grow with a decline in the policy rates and with an advancement of aging.

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Price, Catherine Waddams, Terry Barker, Paul Ekins y Nick Johnstone. "Global Warming and Energy Demand." Economic Journal 106, n.º 436 (mayo de 1996): 727. http://dx.doi.org/10.2307/2235589.

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Baxter, Lester W. y Kevin Calandri. "Global warming and electricity demand". Energy Policy 20, n.º 3 (marzo de 1992): 233–44. http://dx.doi.org/10.1016/0301-4215(92)90081-c.

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Vrancart, Al. "Global demand for cards continues". Card Technology Today 19, n.º 3 (marzo de 2007): 10–11. http://dx.doi.org/10.1016/s0965-2590(07)70058-0.

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Murakami, Ken. "Global Market Pulp Demand & Supply". JAPAN TAPPI JOURNAL 76, n.º 8 (2022): 721–25. http://dx.doi.org/10.2524/jtappij.76.721.

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Tesis sobre el tema "Global demand"

Alsalous, Osama. "Global Demand Forecast Model". Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/78331.

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Air transportation demand forecasting is a core element in aviation planning and policy decision making. NASA Langley Research Center addressed the need of a global forecast model to be integrated into the Transportation Systems Analysis Model (TSAM) to fulfil the vision of the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters to develop a picture of future demand worldwide. Future forecasts can be performed using a range of techniques depending on the data available and the scope of the forecast. Causal models are widely used as a forecasting tool by looking for relationships between historical demand and variables such as economic and population growth. The Global Demand Model is an econometric regression model that predicts the number of air passenger seats worldwide using the Gross Domestic Product (GDP), population, and airlines market share as the explanatory variables. GDP and Population are converted to 2.5 arc minute individual cell resolution and calculated at the airport level in the geographic area 60 nautical miles around the airport. The global demand model consists of a family of models, each airport is assigned the model that best fits the historical data. The assignment of the model is conducted through an algorithm that uses the R2 as the measure of Goodness-of-Fit in addition to a sanity check for the generated forecasts. The output of the model is the projection of the number of seats offered at each airport for every year up to the year 2040.
Master of Science

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Ozkaya, Evren. "Demand management in global supply chains". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26617.

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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Keskinocak, Pinar; Committee Co-Chair: Vande Vate, John; Committee Member: Ferguson, Mark; Committee Member: Griffin, Paul; Committee Member: Swann, Julie. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Lee, Esther S. M. Massachusetts Institute of Technology. "Global demand transparency in the ABB supply chain". Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/75661.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 80).
This paper attempts to provide a solution to a problem facing many multinational firms: the lack of an accessible and comprehensive database for up-to-date component part forecasts. We consider this problem in the context of ABB BU DMPE. After considering various requirements and constraints regarding the consolidation of forecasting information, we propose a novel combination of standardized process and the use of certain IT tools as a first step. After a test run, we discovered that consolidation of forecasting information increases transparency within the supply chain. As a corollary result of our pilot program, we propose that prior to any attempt at consolidation, enforcement of a standardized form and method of forecasting at the local level.
by Esther Lee.
M.B.A.
S.M.

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Freire, Burgos Edwin R. "Aviation Global Demand Forecast Model Development: Air Transportation Demand Distribution and Aircraft Fleet Evolution". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/81313.

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The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. This research project intends to enhance the GDM capabilities. A Fratar model is implemented for the distribution of the forecast demand during each year. The Fratar model uses a 3,974 by 3,974 origin-destination matrix to distribute the demand among 55,612 unique routes in the network. Moreover, the GDM is capable to estimate the aircraft fleet mix per route and the number of flights per aircraft that are needed to satisfy the forecast demand. The model adopts the aircraft fleet mix from the Official Airline Guide data for the year 2015. Once the aircraft types are distributed and flights are assigned, the GDM runs an aircraft retirement and replacement analysis to remove older generation aircraft from the network and replace them with existing or newer aircraft. The GDM continues to evolve worldwide aircraft fleet by introducing 14 new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA.
Master of Science
The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. The previous study done by Alsaous, predicts how many seats will be departing out of the 3,974 airports worldwide. This project intends to use the outputs of the GDM and distribute the seats predicted among the airports. The objective is to predict how many seats will be offered that will be departing from airport “A” and arriving at airport “B”. For this, a Fratar model was implemented. The second objective of this project is to estimate what will the aircraft fleet be in the future and how many flights will be needed to satisfy the predicted air travel demand. If the number of seats going from airport A to airport B is known, then, by analyzing real data it can be estimated what type of aircraft will be flying from airport “A” to airport “B” v and how many flights each aircraft will have to perform in order to satisfy the forecasted demand. Besides of estimating the type of aircraft that will be used in the future, the modeled created is capable of introducing new aircraft that are not part of the network yet. Fourteen new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA.

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Radcliffe, Nicholas Ryan. "Adjusting Process Count on Demand for Petascale Global Optimization". Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/36349.

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There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running at the petascale are likely to be memory intensive, which makes thrashing a serious problem for many petascale applications. One way to overcome this challenge is to use a dynamic number of processes, so that the total amount of memory available for the computation can be increased on demand. This thesis describes modifications made to the massively parallel global optimization code pVTdirect in order to allow for a dynamic number of processes. In particular, the modified version of the code monitors memory use and spawns new processes if the amount of available memory is determined to be insufficient. The primary design challenges are discussed, and performance results are presented and analyzed.
Master of Science

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Cao, Yu. "Long-distance procurement planning in global sourcing". Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2015. http://www.theses.fr/2015ECAP0015/document.

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Cette thèse porte sur l’optimisation de l’approvisionnement dans les zones géographiquement lointaines. Au moment de planiﬁer des approvisionnements de matières premières ou de composants dans des pays lointains, la longue distance géographique entre l’acheteur et le fournisseur devient un enjeu essentiel à prendre en compte. Puisque le transport se fait souvent par la voie maritime, le délai d’approvisionnement est si long que les besoins peuvent évoluer pendant la longue période de livraison, ce qui peut engendrer un risque de rupture élevé. Cette thèse présente des approches adaptatives aﬁn d’élaborer des plans d’approvisionnements lointains d’une manière rentable. Tout d’abord, nous proposons un cadre d’adaptation de la planiﬁcation des approvisionnements lointains. Il déploie des techniques de prévision de la demande et des méthodes d’optimisation d’approvisionnements à horizon glissant. En utilisant ce cadre, nous transformons le problème de la planiﬁcation sur l’horizon globale en plusieurs problèmes standards de lotissement avec demandes stochastiques sur des sous-horizons. Ce cadre permet aussi d’évaluer la performance sur une longue période des méthodes utilisées. Nous considérons ensuite la planiﬁcation optimale d’approvisionnement sur les sous-horizons. Deux hypothèses de ruptures de stocks sont considérées: livraison tardive et vente perdue (ou sous-traitance). Nous développons des approches optimales ou quasi-optimales pour faire des plans d’approvisionnement tout en minimisant les coûts totaux prévus de commande, de stockage et de rupture sur les sous-horizons. Les méthodes proposées peuvent servir de repères pour évaluer d’autres méthodes. Pour chaque hypothèse, nous menons des expériences numériques pour évaluer les algorithmes développés et les approches adaptatives de planiﬁcation globales. Les résultats expérimentaux montrent bien leur efficacité
This research discusses procurement planning problems engaged in global sourcing. The main difficulty is caused by the geographically long distance between buyer and supplier, which results in long lead times when maritime transport is used. Customer demands of ﬁnished products usually evolve during the shipment, thus extra costs will be produced due to unpredictable overstocks or stockouts. This thesis presents adaptive planning approaches to make adequate long-distance procurement plans in a cost-efficient manner. Firstly, an adaptive procurement planning framework is presented. The framework deploys demand forecasting and optimal planning in a rolling horizon scheme. In each subhorizon, demands are assumed to follow some known distribution patterns, while the distribution parameters will be estimated based on up-to-date demand forecasts and forecast accuracy. Then a portable processing module is presented to transform the sub-horizon planning problem into an equivalent standard lot-sizing problem with stochastic demands.Secondly, optimal or near-optimal procurement planning methods are developed to minimize expected total costs including setup, inventory holding and stockout penalty in subhorizons. Two extreme stockout assumptions are considered: backorder and lost sale (or outsourcing). The proposed methods can serve as benchmarks to evaluate other methods. Numerical tests have validated the high efficiency and effectiveness of both sub-horizon planning methods and the overall adaptive planning approaches

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McElroy, Wade Allen. "Demand prediction modeling for utility vegetation management". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117973.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 63-64).
This thesis proposes a demand prediction model for utility vegetation management (VM) organizations. The primary uses of the model is to aid in the technology adoption process of Light Detection and Ranging (LiDAR) inspections, and overall system planning efforts. Utility asset management ensures vegetation clearance of electrical overhead powerlines to meet state and federal regulations, all in an effort to create the safest and most reliable electrical system for their customers. To meet compliance, the utility inspects and then prunes and/or removes trees within their entire service area on an annual basis. In recent years LiDAR technology has become more widely implemented in utilities to quickly and accurately inspect their service territory. VM programs encounter the dilemma of wanting to pursue LiDAR as a technology to improve their operations, but find it prudent, especially in the high risk and critical regulatory environment, to test the technology. The biggest problem during, and after, the testing is having a baseline of the expected number of tree units worked each year due to the intrinsic variability of tree growth. As such, double inspection and/or long pilot projects are conducted before there is full adoption of the technology. This thesis will address the prediction of circuit-level tree work forecasting through the development a model using statistical methods. The outcome of this model will be a reduced timeframe for complete adoption of LiDAR technology for utility vegetation programs. Additionally, the modeling effort provides the utility with insight into annual planning improvements. Lastly for later usage, the model will be a baseline for future individual tree growth models that include and leverage LiDAR data to provide a superior level of safety and reliability for utility customers.
by Wade Allen McElroy.
M.B.A.
S.M.

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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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Holbrook, Blair Sato. "Point-of-sale demand forecasting". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104397.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 38).
Nike Always Available (AA) is a significant global business unit within Nike that allows retail customers to purchase athletic essentials at weekly replenishment intervals and 95% availability. However, demand fluctuations and current forecasting processes have resulted in frequent stock-outs and inventory surpluses, which in turn affect revenue, profitability, and brand trust. Potential root causes for demand fluctuations have included: -- Erratic customer behavior, including unplanned promotional events, allocation of open-to- buy dollars for futures (i.e., contract) versus replenishment (i.e., AA), and product inventory loading to protect from anticipated stock-outs; -- Lack of incentives and accountability to encourage accurate forecasting by customers. Current forecasting processes, which utilize historical sell-in data (i.e., product sold to retail customers) were found to be significantly inaccurate - 100% MAPE. The goal of this project was to develop a more accurate forecast based on historical sell-through data (i.e., product sold to consumers), which were recently made available. Forecast error was drastically reduced using the new forecasting method - 35% MAPE. A pilot was initiated with a major retail customer in order to test the new forecast model and determine the effects of a more transparent ordering partnership. The pilot is ongoing at the time of thesis completion.
by Blair Sato Holbrook.
M.B.A.
S.M. in Engineering Systems

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Bornelind, Patrik. "Challenges in forecasting management for global companies". Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264218.

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In today’s fast-moving world, a company´s ability to align with changes in the market is becoming a major competitive factor. Demand forecasting form the basis of all supply chain planning and is a process that companies often fail to recognize as a key contributor to corporate success. Different contexts and market dynamics creates different challenges for companies to overcome in order to have an efficient forecasting process, matching demand with supply. This master thesis looks at the whole forecasting process, also called forecasting management, at a decentralized global company to identify the main challenges within the process and propose recommendations on how to overcome them. The research is based on a single case study where the forecasting process is investigated using four different dimensions: Functional Integration, Approach, Systems and Performance Measurements. The study identified twelve challenges in the forecasting process where a majority can be connected to issues within information sharing and lack of support in the process. Based on the identified challenges, eight improvement suggestions where developed to target the challenges and improving the process for a decentralized global company.
I dagens snabbt utvecklande och växande landskap så är ett företags förmåga att anpassa sig till marknadens behov en betydande konkurrensfaktor. Säljprognoser utgör grunden för all planering inom försörjningskedjan och är en process som företag ofta inte erkänner som en viktig bidragsgivare till företagets framgång. Olika marknadslandskap och förutsättningar skapar olika utmaningar för företag att bemästra för att kunna bedriva ett effektivt prognosarbete och matcha efterfrågan med utbud. Detta examensarbete tittar på hela prognosprocessen, även kallad prognoshantering, hos ett decentraliserat globalt företag för att identifiera de viktigaste utmaningarna i processen och föreslå rekommendationer om hur man kan övervinna dem. Forskningen bygger på en enda fallstudie där prognosprocessen undersöks utifrån fyra olika dimensioner: Funktionell integration, strategi, system och prestandamätningar. Studien identifierade tolv utmaningar i prognosprocessen där en majoritet kan kopplas till utmaningar inom informationsdelning och brist på stöd i processen. Baserat på de identifierade utmaningarna utvecklades åtta förbättringsåtgärder för att övervinna utmaningarna och förbättra processen för ett decentraliserat globalt företag.

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Libros sobre el tema "Global demand"

Jetin, Bruno, ed. Global Automobile Demand. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145.

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Jetin, Bruno, ed. Global Automobile Demand. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516176.

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Kursunoglu, Behram N., Stephan L. Mintz y Arnold Perlmutter, eds. Global Energy Demand in Transition. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1048-6.

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Terry, Barker, Ekins Paul y Johnstone Nick 1965-, eds. Global warming and energy demand. London: Routledge, 1995.

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Buchinsky, Moshe. Modelling global demand for fertilizer. [s.l.]: World Bank, 1987.

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Indian chemical industry: Exploring global demand. Mumbai: Export-Import Bank of India, 2012.

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Krissoff, Barry, Mary Bohman y Julie A. Caswell, eds. Global Food Trade and Consumer Demand for Quality. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-5329-5.

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L, Delgado Christopher y International Food Policy Research Institute., eds. Outlook for fish to 2020: Meeting global demand. Washington, D.C: International Food Policy Research Institute, 2003.

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Montgomery, David Bruce. Demand for and use of global account management. Cambridge, MA: Marketing Science Institute, 1999.

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Crastan, Valentin. Global Energy Demand and 2-degree Target, Report 2014. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12310-3.

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Capítulos de libros sobre el tema "Global demand"

Jetin, Bruno. "Introduction". En Global Automobile Demand, 1–9. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_1.

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Jetin, Bruno. "The US Automobile Market after the “Great Recession”: Back to Business as Usual or Birth of a New Industry?" En Global Automobile Demand, 10–36. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_2.

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Pardi, Tommaso. "A Model to Follow? The Impact of Neoliberal Policies on the British Automobile Market and Industry". En Global Automobile Demand, 37–71. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_3.

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Jullien, Bernard. "Excess Capacity Viewed as Excess Quality — The Case of French Car Manufacturing". En Global Automobile Demand, 72–104. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_4.

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Blöcker, Antje y Julia Hildermeier. "Income Polarisation, Rising Mobility Costs and Green Transport: Contradictory Developments in Germany’s Automotive Market". En Global Automobile Demand, 105–26. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_5.

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Köhler, Holm-Detlev y José Pablo Calleja Jiménez. "The Automobile Demand in Spain". En Global Automobile Demand, 127–50. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_6.

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Bungsche, Holger. "Japan’s Automobile Market in Troubled Times". En Global Automobile Demand, 151–78. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_7.

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Chung, Myeong-kee. "From Expansion to Mature: Turning Point of the Korean Automotive Market". En Global Automobile Demand, 179–201. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_8.

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Jetin, Bruno. "Conclusion". En Global Automobile Demand, 202–3. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516145_9.

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Jetin, Bruno. "Introduction". En Global Automobile Demand, 1–11. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137516176_1.

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Actas de conferencias sobre el tema "Global demand"

Ruddy, Jonathan y Mark O'Malley. "Global shifting of data centers demand". En 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). IEEE, 2014. http://dx.doi.org/10.1109/isgteurope.2014.7028880.

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Dash, Ritesh, S. M. Ali, Aryadhara Pradhan y Anoop Kumar Mohanta. "Hybrid System for Meeting Global Energy Demand". En 2015 IEEE International Conference on Computational Intelligence & Communication Technology (CICT). IEEE, 2015. http://dx.doi.org/10.1109/cict.2015.69.

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Al Qubali, Abdulaziz Kamal. "Global Demand of Nonmetallic Applications in Construction". En SPE EuropEC - Europe Energy Conference featured at the 83rd EAGE Annual Conference & Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209693-ms.

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Abstract The global market in construction is forecasts a demand growth for nonmetallic applications to replace conventional metallic materials. of the current produced plastic, around 367 million tons, 20.4% of this demand is utilized in building and construction. According to research on European demand, these numbers will continue to grow over the next decade, especially for polyethylene, polypropylene and polyvinyl chloride (PVC). Different applications have already proven their efficiency in terms of OPEX and sometimes CAPEX as well. This dramatic growth in the plastic market will lead to supplying these materials to different markets, which will result in more nonmetallic applications for the construction sector.

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Morrison, Aiden J. "Global Demand Projections for Renewable Energy Resources". En 2007 IEEE Canada Electrical Power Conference (EPC 2007). IEEE, 2007. http://dx.doi.org/10.1109/epc.2007.4520389.

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Tzanidakis, Konstantinos, Christos Malavazos, Kostas Tsatsakis, Antonis Papanikolaou, Tasos Tsitsanis y Brendan O'Flynn. "Optimized Consumer-Centric Demand Response". En 2018 Global Internet of Things Summit (GIoTS). IEEE, 2018. http://dx.doi.org/10.1109/giots.2018.8534542.

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Freire Burgos, Edwin R., Antonio Trani, Nicolas Hinze, Ty Marien, Karl Geiselhart, Samuel Dollyhigh y Jonathan Seidel. "Global Demand Model to Estimate Supersonic Commercial Services". En AIAA AVIATION 2020 FORUM. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-3260.

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Kozman, Jess B. "Data on Demand: The Emerging Global Business Case". En SPE Middle East Oil and Gas Show and Conference. Society of Petroleum Engineers, 2005. http://dx.doi.org/10.2118/93625-ms.

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Freire Burgos, Edwin R., Antonio Trani, Nicolas Hinze, Ty Marien, Karl Geiselhart, Samuel Dollyhigh y Jonathan Seidel. "Global Demand Model to Estimate Supersonic Commercial Services". En AIAA AVIATION 2021 FORUM. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-3187.

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Nambi S. N., Akshay Uttama, Antonio R. Lua y Venkatesha Prasad R. "Decentralized Energy Demand Regulation in Smart Homes". En 2016 IEEE Global Communications Conference (GLOBECOM). IEEE, 2016. http://dx.doi.org/10.1109/glocom.2016.7841718.

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Dashevskiy, Mikhail y Zhiyuan Luo. "Network Traffic Demand Prediction with Confidence". En IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference. IEEE, 2008. http://dx.doi.org/10.1109/glocom.2008.ecp.284.

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Informes sobre el tema "Global demand"

Jeanne, Olivier. Currency Wars, Trade Wars, and Global Demand. Cambridge, MA: National Bureau of Economic Research, diciembre de 2021. http://dx.doi.org/10.3386/w29603.

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Amiti, Mary, Patrick McGuire y David Weinstein. Supply- and Demand-side Factors in Global Banking. Cambridge, MA: National Bureau of Economic Research, junio de 2017. http://dx.doi.org/10.3386/w23536.

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Amarasinghe, U. A. y V. Smakhtin. Global water demand projections: past, present and future. International Water Management Institute (IWMI)., 2014. http://dx.doi.org/10.5337/2014.212.

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Cranfield, John, Thomas Hertel, James Eales y Paul Preckel. Changes in the Structure of Global Food Demand. GTAP Working Paper, septiembre de 2000. http://dx.doi.org/10.21642/gtap.wp01.

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A newly developed demand system is used to estimate the response of food and food product demand to per capita expenditure changes. The resulting Engel elasticities are then used to project food and food product demand in 2020 assuming per capita expenditure and population changes. Results suggest that while food expenditure is projected to grow, it accounts for a smaller proportion of total expenditure. Further analysis indicates change in the composition of food demand away from a grain and towards livestock is projected to occur in lower income countries in 2020.

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Yu, Wusheng, Thomas Hertel, Paul Preckel y James Eales. Projecting World Food Demand Using Alternative Demand Systems. GTAP Working Paper, febrero de 2003. http://dx.doi.org/10.21642/gtap.wp21.

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Computable General Equilibrium (CGE) models are increasingly being used to project world food markets in order to support forward-looking policy analysis. Such projections hinge critically on the underlying functional form for representing consumer demand. Simple functional forms can lead to unrealistic projections by failing to capture changes in income elasticities of demand. We adopt as our benchmark the recently introduced AIDADS demand system and compare it with several alternative demand systems currently in widespread use in CGE models. This comparison is conducted in the context of projections for disaggregated global food demand using a global CGE model. We find that AIDADS represents a substantial improvement, particularly for the rapidly growing developing countries. For these economies, the most widely used demand systems tend to over-predict future food demands, and hence overestimate future production and import requirements for agricultural products.

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Koijen, Ralph S. y Motohiro Yogo. Exchange Rates and Asset Prices in a Global Demand System. Cambridge, MA: National Bureau of Economic Research, junio de 2020. http://dx.doi.org/10.3386/w27342.

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Sands, Ronald (Ronald D. )., Birgit Meade, James L. Seale, Sherman Robinson y Riley Seeger. Scenarios of global food consumption. Washington, D.C: Economic Research Service, U.S. Department of Agriculture, septiembre de 2023. http://dx.doi.org/10.32747/2023.8134356.ers.

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The global land base is under increasing pressure to provide food for a growing population. This report describes how increasing population, income, and agricultural productivity may affect global production and consumption of crops and food products by 2050. Results show that in an income-driven food demand scenario, production of world crop calories increases by 47 percent from 2011 to 2050. Demand for food calories and crop calories increases over time in all scenarios, with most of the adjustment through increases in crop yield (intensification). The amount of cropland also increases (extensification) but less on a percentage basis

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Seppänen, Sampo, Hanna-Mari Ahonen, Juha Ollikainen, Suvi Viljaranta, Jelmer Hoogzaad, Suzy Huber, Darragh Conway, Thiago Chagas y Mercedes Fernandez. Demand in a Fragmented Global Carbon Market: Outlook and Policy Options. Nordic Council of Ministers, marzo de 2013. http://dx.doi.org/10.6027/tn2013-525.

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Cesa-Bianchi, Ambrogio. Housing Cycles and Macroeconomic Fluctuations: A Global Perspective. Inter-American Development Bank, octubre de 2012. http://dx.doi.org/10.18235/0011417.

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This paper investigates the international spillovers of housing demand shocks on real economic activity. The global economy is modeled using a Global VAR, with a novel house price data set for both advanced and emerging economies. The impulse responses to an identified US housing demand shock confirm the existence of strong international spillovers to advanced economies. In contrast, the response of some major emerging economies is not significantly different from zero. The paper also shows that synchronized housing demand shocks in advanced economies reinforce each other and have a deep and long-lasting impact on economic activity.

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di Giovanni, Julian, Şebnem Kalemli-Özcan, Alvaro Silva y Muhammed A. Yıldırım. Pandemic-Era Inflation Drivers and Global Spillovers. Federal Reserve Bank of New York, noviembre de 2023. http://dx.doi.org/10.59576/sr.1080.

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We estimate a multi-country, multi-sector New Keynesian model to quantify the drivers of domestic inflation during 2020–23 in several countries, including the United States. The model matches observed inflation together with sector-level prices and wages. We further measure the relative importance of different types of shocks on inflation across countries over time. The key mechanism, the international transmission of demand, supply and energy shocks through global linkages helps us to match the behavior of the USD/EUR exchange rate. The quantification exercise yields four key findings. First, negative supply shocks to factors of production, labor and intermediate inputs, initially sparked inflation in 2020-21. Global supply chains and complementarities in production played an amplification role in this initial phase. Second, positive aggregate demand shocks, due to stimulative policies, widened demand-supply imbalances, amplifying inflation further during 2021-22. Third, the reallocation of consumption between goods and service sectors, a relative sector-level demand shock, played a role in transmitting these imbalances across countries through the global trade and production network. Fourth, global energy shocks have differential impacts on the U.S. relative to other countries’ inflation rates. Further, complementarities between energy and other inputs to production play a particularly important role in the quantitative impact of these shocks on inflation.

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