Academic literature on the topic 'Resource efficiency and elasticity'
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Journal articles on the topic "Resource efficiency and elasticity"
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P. Christopher. "AI-Driven Resource Provisioning: Enhancing Elasticity and Efficiency with Hybrid RNN-LSTM Models." Advances in Nonlinear Variational Inequalities 28, no. 2 (2024): 72–83. http://dx.doi.org/10.52783/anvi.v28.1852.
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Automatic resource provisioning techniques that dynamically modify resources in response to service demand are essential to implementing elasticity services. For systems with strict latency or reaction time requirements, such as Enterprise Resource Planning (ERP) systems under high traffic loads, this flexibility is crucial for lowering power consumption and guaranteeing quality of service (QoS). Determining the best point at which to scale resources is still a difficult task. In this research, we provide an AI-integrated system that adjusts resources according to anticipated demand. To predict load requests, the system uses an LSTM model and a Hybrid Recurrent Neural Network (RNN). This strategy seeks to minimize overprovisioning, which will lower the cost of infrastructure and energy usage. The deep learning model aims to estimate the resources required to improve service response time and satisfy customer requests, as well as to anticipate with high accuracy the processing load of distributed servers. Proactive provisioning decisions are made for the servers based on the anticipated load. Our tests on a common server request dataset show that the suggested RNN+LSTM model performs better than traditional deep learning models in terms of efficient resource management and prediction accuracy.
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Yang, Shiliang, Huimin Wang, Jinping Tong, Jianfeng Ma, Fan Zhang, and Shijuan Wu. "Technical Efficiency of China’s Agriculture and Output Elasticity of Factors Based on Water Resources Utilization." Water 12, no. 10 (2020): 2691. http://dx.doi.org/10.3390/w12102691.
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A stochastic frontier approach (SFA) model of translog production function was constructed to analyze the growth effect of agricultural production factors on grain production in China. Under the condition of unchanged cultivated land, the agricultural labor, capital, and water were regarded as input elements of the agricultural production function. The maximum likelihood estimation (MLE) method was used to analyze the technical efficiency, output elasticity, substitution elasticity, and relative variability of grain production in China from 2004 to 2018. The results showed that: (1) For the technical efficiency and output elasticity of the input factors of grain production, there were significant differences in different provinces. For example, the water resource was insufficient in Beijing and Shanghai, but the output elasticity of water was high. Heilongjiang was rich in water and had high technical efficiency. For Xinjiang, water was sufficient, but its output elasticity was deficient and the technical efficiency didn’t increase. (2) The overall technical efficiency level was relatively low and was still declining year by year; the output elasticity of water was much greater than that of capital. There was still great potential for grain growth. (3) Optimizing resource allocation and controlling the appropriate ratio of input factors to develop grain production could achieve the maximum benefits. Finally, according to the empirical results, this paper put forward some practical policy suggestions for optimizing the allocation of input factors, especially water and capital, which can ultimately improve agricultural productivity by improving technical efficiency.
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Cui, Yu Quan, Xi Lu, and Lin Lin Li. "Resource Allocation Problem Based on Weighted Cross-Efficiency and Production Capacity." Applied Mechanics and Materials 392 (September 2013): 919–24. http://dx.doi.org/10.4028/www.scientific.net/amm.392.919.
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In economic development, resource has become increasingly important and the problem of how to allocate resource reasonably has become a hot issue..This paper proposes a new resource allocation mode based on DEA models taking into account production efficiency, input-output elasticity, potential production capacity. We put forwards a new weighted cross-efficiency calculation formula and a new resource allocation weights calculation formula. From the numerical example, the result is satisfactory.
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Haie, Naim, Gaspar J. B. Q. A. Machado, Rui M. Pereira, and Andrew A. Keller. "Effective efficiency in water resources management using efficiency elasticity index." Water and Environment Journal 25, no. 4 (2011): 532–39. http://dx.doi.org/10.1111/j.1747-6593.2011.00252.x.
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Moh'd, Z. Freaj, and Sleit Azzam. "Hybrid Approach for Resource Provisioning in Cloud Computing." Journal of Information Sciences and Computing Technologies 6, no. 1 (2016): 546–61. https://doi.org/10.5281/zenodo.3968238.
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Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Elasticity of resources is considered as a key characteristic of cloud computing using this key characteristic; internet services are allocated the onlyneeded resources. This allocation of resources however should not be at the expense of the services’ performance. Allocation of resources without degrading performance is called resource provisioning. Resource provisioning does not only support the elasticity of resources, but also enhances cost efficiency and sustainability. The goal of this work is to investigate resource provisioning to increase the percentage of resources utilization without degrading the performance so that the power consumption of the cloud data centers is reduced. To achieve this goal, a hybrid-approach for resource provisioning is developed. In this approach, a list of virtual machines is requested, passed to a selection algorithm, sorting the machines according to their load, compute the threshold of the machines’ load, and combining the high load with low load from two different virtual machines on one super virtual machine. The approach was implemented in a simulator called CloudSim. It was used to run two sets of experiments. The first is to measure the power consumption of the data center as whole and hosts as well. And the second is concerned with the processing times and memory usage. The results have shown that this approach outperforms traditional counterparts in resource provisioning. The results showed that the hybrid approach achieved reduction of (5.85 MW/s) in power consumption compared with the traditional counterparts for the whole data center, as well as reduction of (2.48 MW/s) in power consumption for the hosts.
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Hanafy, Walid A., Qianlin Liang, Noman Bashir, David Irwin, and Prashant Shenoy. "CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency." Proceedings of the ACM on Measurement and Analysis of Computing Systems 7, no. 3 (2023): 1–28. http://dx.doi.org/10.1145/3626788.
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Cloud platforms are increasing their emphasis on sustainability and reducing their operational carbon footprint. A common approach for reducing carbon emissions is to exploit the temporal flexibility inherent to many cloud workloads by executing them in periods with the greenest energy and suspending them at other times. Since such suspend-resume approaches can incur long delays in job completion times, we present a new approach that exploits the elasticity of batch workloads in the cloud to optimize their carbon emissions. Our approach is based on the notion of "carbon scaling," similar to cloud autoscaling, where a job dynamically varies its server allocation based on fluctuations in the carbon cost of the grid's energy. We develop a greedy algorithm for minimizing a job's carbon emissions via carbon scaling that is based on the well-known problem of marginal resource allocation. We implement a CarbonScaler prototype in Kubernetes using its autoscaling capabilities and an analytic tool to guide the carbon-efficient deployment of batch applications in the cloud. We then evaluate CarbonScaler using real-world machine learning training and MPI jobs on a commercial cloud platform and show that it can yield i) 51% carbon savings over carbon-agnostic execution; ii) 37% over a state-of-the-art suspend-resume policy; and iii) 8 over the best static scaling policy.
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Varchenko, Olga Myronivna, Kateryna Vitalyivna Tkachenko, Valentyna Anatolyivna Byba, and Nadiia Ivanivna Svynous. "Features of Formation and Use of Production Resources by Small Farms in Ukraine." Visegrad Journal on Bioeconomy and Sustainable Development 8, no. 2 (2019): 69–74. http://dx.doi.org/10.2478/vjbsd-2019-0013.
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Abstract It is proved that the effective development of small farms is ensured by the level of their resource supply and the balance of production resources, the efficiency of which we have been carried out on the basis of the calculation of allocative and technical efficiency. According to the obtained equation of production function, we conclude that the most elastic factor is the cost of seeds, fertilizers, feed and other material costs. An increase of this resource by 1% will lead to an increase in the result by 0.395%. The smallest value of the coefficient of elasticity was obtained from such production resource as arable land. The obtained model shows that there is a decreasing effect on the scale, since the sum of the regression coefficients is less than 1 (equal to 0.962), which means that if the resources increase in some proportion, then the volumes of revenue increase in a smaller proportion. It is substantiated that allocative inefficiency is caused not by the excessive use of resources in small farms, but by the higher prices for them and the underestimated agricultural output.
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GUPTA, ARPIT, and KASHIKA ARORA. "EVALUATING THE ELASTICITY OF SUBSTITUTION BETWEEN CAPITAL AND LABOUR (BOTH SKILLED AND UNSKILLED) IN THE INDIAN MANUFACTURING SECTOR." Review of Economic and Business Studies 17, no. 1 (2024): 81–102. https://doi.org/10.47743/rebs-2024-1-0004.
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This study investigates the dynamics of the elasticity of substitution between capital and labour, both skilled and unskilled, across sixteen key industries in India's manufacturing sector. Employing a Constant Elasticity of Substitution (CES) production function and utilizing panel data spanning from 2001 to 2017, the research employs panel cointegration techniques to establish a long-term relationship between the variables. The study calculates long-run elasticity through FMOLS and DOLS estimators, revealing that in India's manufacturing sector, the elasticity of substitution between capital and skilled labour is higher compared to that between capital and unskilled labour, as consistently indicated by both estimators. These findings bear significant implications for industry-level resource allocation and labour market policies, suggesting a need for targeted strategies to enhance the integration and efficiency of skilled labour within the manufacturing sector.
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Wang, Jianying, Tongliang Li, Haoze Song, et al. "PolarDB-IMCI: A Cloud-Native HTAP Database System at Alibaba." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–25. http://dx.doi.org/10.1145/3589785.
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Cloud-native databases have become the de-facto choice for mission-critical applications on the cloud due to the need for high availability, resource elasticity, and cost efficiency. Meanwhile, driven by the increasing connectivity between data generation and analysis, users prefer a single database to efficiently process both OLTP and OLAP workloads, which enhances data freshness and reduces the complexity of data synchronization and the overall business cost. In this paper, we summarize five crucial design goals for a cloud-native HTAP database based on our experience and customers' feedback, i.e., transparency, competitive OLAP performance, minimal perturbation on OLTP workloads, high data freshness, and excellent resource elasticity. As our solution to realize these goals, we present PolarDB-IMCI, a cloud-native HTAP database system designed and deployed at Alibaba Cloud. Our evaluation results show that PolarDB-IMCI is able to handle HTAP efficiently on both experimental and production workloads; notably, it speeds up analytical queries up to ×149 on TPC-H (100GB). PolarDB-IMCI introduces low visibility delay and little performance perturbation on OLTP workloads (<5%), and resource elasticity can be achieved by scaling out in tens of seconds.
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Bhai, Shashank, R. R. Kushwaha, Supriya, et al. "Assessment of Resources Use Efficiency and Challenges of Rapeseed-Mustard Crop in Prayagraj District of Uttar Pradesh, India." Journal of Experimental Agriculture International 47, no. 6 (2025): 343–50. https://doi.org/10.9734/jeai/2025/v47i63494.
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In the present paper, an attempt has been made to examine Rapeseed-Mustard cropcultivation in different categories of farmers in Prayagraj District of Uttar Pradesh. Primary data was collected through personal interview by pre-structured and pre-tested schedule; the data was collected for the agricultural year 2022-23. A sample size of 100 farmers, marginal (48) Small (31) Medium (21) were interviewed form 5 village of Baharia block in prayagraj district select the farmers by using the proportionate allocation method. This study evaluates the resource use efficiency in rapeseed-mustard cultivation across different farm sizes, focusing on marginal, small, and medium farms. The analysis reveals that marginal farms exhibit the highest production elasticity for inputs X1, X2, and X5, indicating significant responsiveness in production with the increase of these inputs. Small farms show the highest elasticity for X3, while medium farms generally demonstrate lower production elasticity across all input variables. The sum of elasticity/return to scale is greatest in marginal farms, suggesting higher operational efficiency, followed by small and then medium farms. The R² values suggest the regression models explain 79%, 83%, and 85% of production variability for marginal, small, and medium farms, respectively, indicating the best model fit for medium farms. Marginal Value Productivity (MVP) data shows that investment in all inputs can yield higher returns, with notable variances across farm sizes. Key constraints to rapeseed-mustard production include high input costs, fertilizer shortages, and labor availability. Recommendations include education on pesticide use, cost reduction strategies, organic waste recycling for compost, and establishing community credit systems. Implementing these measures could enhance production efficiency and increase rapeseed-mustard yields.
Dissertations / Theses on the topic "Resource efficiency and elasticity"
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Rezagholi, Mahmoud. "Cost-Efficient Designs for Assessing Work-Related Biomechanical Exposures." Doctoral thesis, Uppsala universitet, Institutionen för medicinska vetenskaper, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-185526.
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Work-related disorders due to biomechanical exposures have been subject to extensive research. Studies addressing these exposures have, however, paid limited attention to an efficient use of resources in exposure assessment. The present thesis investigates cost-efficient procedures for assessment of work-related biomechanical exposures, i.e. procedures aiming at a proper balance between statistical and economic performance. Paper I is a systematic review of tools used in literature providing cost-efficient data collection designs. Two main approaches were identified in nine publications, i.e. comparing cost efficiency among alternative data collection designs, and optimizing resource allocation between different stages of data collection, e.g. subjects and samples within subjects. The studies presented, in general, simplified analyses, in particular with respect to economics. Paper II compared the cost-efficiency of four video-based techniques for assessing upper arm postures. The comparison was based both on a comprehensive model of cost and error and additionally on two simplified models. Labour costs were a dominant factor in the cost efficiency comparison. Measurement bias and costs other than labour cost influenced the rank and economic evaluation of the assessment techniques. Paper III compared the cost efficiency of different combinations of direct and indirect methods for exposure assessments. Although a combination of methods could significantly reduce the total cost of obtaining a desired level of precision, the total cost was, in the investigated scenario, lowest when only direct measurements were performed. However, when the total number of measurements was fixed, a combination was the most cost efficient choice. In Paper IV, demand functions were derived for a four-stage measurement strategy with the focus of either minimizing the cost for a required precision, or maximizing the precision for a predetermined budget. The paper presents algorithms for identifying optimal values of measurement inputs at all four stages, adjusted to integers, as necessary for practical application. In summary, the thesis shows that it is important to address all sources of costs and errors associated with alternative measurement designs in any particular study, and that an optimal determination of samples at different stages can be identified in several cases not previously addressed in the literature.
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Gonzalez, Hernandez Ana. "Site-level resource efficiency analysis." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/284771.
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To achieve agreed targets for reducing global carbon emissions, industry must become more resource-efficient. To this end, two viable strategies exist: energy efficiency and material efficiency. Despite their inherent interdependence, industry continues to treat these two strategies as isolated pursuits, providing in the process only a partial insight into the potential of resource efficiency. To resolve this disconnect, this thesis attempts to develop and apply tools that help integrate industrial energy and material efficiency analyses. Three areas of research are explored. The first is concerned with a fundamental component of industrial performance: efficiency benchmarks. No agreed-upon metric exists to measure the efficiency with which the sector trans- forms both energy and materials - that is, how resource-efficient they are. This thesis applies exergy - a well-established method to consolidate energy and materials into a single metric - to a case study of the global steel industry in 2010. Results show that this exergy-based metric provides a suitable proxy to capture the interactions between energy and materials. By comparing energy and material efficiency options on an equal footing, this metric encourages the recovery of material by-products - an intervention excluded from traditional energy efficiency metrics. To realise resource efficiency opportunities, individual industry firms must be able to identify them at actionable time-frames and scopes. Doing this hinges on understanding resources flows through entire systems, the most detailed knowledge of which resides in control data. No academic study was found to exploit control data to construct an integrated picture of resources that is representative of real operations. In the second research area, control data is extracted to track the resource flows and efficiency of a basic oxygen steel-making plant from TataSteel. This second case study highlights the plant's material efficiency options during operations. It does so by building close-to-real-time Sankey diagrams of resource flows (measured in units of exergy) for the entire plant and its constituent processes. Without the support of effective policies the new exergy approach is unlikely to be widely adopted in industry. By collating evidence from interviews and policy documents, the third area explores why the European Union's industrial energy and emissions policies do not incentivise material efficiency. Results suggest several contributing factors, including: the inadequacy of monitored indicators; an imposed policy lock-in; and the lack of a designated industry lobby and high-level political buy-in. Policy interventions are then proposed to help integrate material efficiency into energy and climate agendas. The European Union's limited agency stresses the need for Member States and industry to drive the move to a low-carbon industry in the short-term.
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Amaral, Marcelo. "Improving resource efficiency in virtualized datacenters." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/666753.
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In recent years there has been an extraordinary growth of the Internet of Things (IoT) and its protocols. The increasing diffusion of electronic devices with identification, computing and communication capabilities is laying ground for the emergence of a highly distributed service and networking environment.
The above mentioned situation implies that there is an increasing demand for advanced IoT data management and processing platforms. Such platforms require support for multiple protocols at the edge for extended connectivity with the objects, but also need to exhibit uniform internal data organization and advanced data processing capabilities to fulfill the demands of the application and services that consume IoT data.
One of the initial approaches to address this demand is the integration between IoT and the Cloud computing paradigm. There are many benefits of integrating IoT with Cloud computing. The IoT generates massive amounts of data, and Cloud computing provides a pathway for that data to travel to its destination. But today’s Cloud computing models do not quite fit for the volume, variety, and velocity of data that the IoT generates.
Among the new technologies emerging around the Internet of Things to provide a new whole scenario, the Fog Computing paradigm has become the most relevant. Fog computing was introduced a few years ago in response to challenges posed by many IoT applications, including requirements such as very low latency, real-time operation, large geo-distribution, and mobility. Also this low latency, geo-distributed and mobility environments are covered by the network architecture MEC (Mobile Edge Computing) that provides an IT service environment and Cloud-computing capabilities at the edge of the mobile network, within the Radio Access Network (RAN) and in close proximity to mobile subscribers. Fog computing addresses use cases with requirements far beyond Cloud-only solution capabilities. The interplay between Cloud and Fog computing is crucial for the evolution of the so-called IoT, but the reach and specification of such interplay is an open problem.
This thesis aims to find the right techniques and design decisions to build a scalable distributed system for the IoT under the Fog Computing paradigm to ingest and process data. The final goal is to explore the trade-offs and challenges in the design of a solution from Edge to Cloud to address opportunities that current and future technologies will bring in an integrated way. This thesis describes an architectural approach that addresses some of the technical challenges behind the convergence between IoT, Cloud and Fog with special focus on bridging the gap between Cloud and Fog. To that end, new models and techniques are introduced in order to explore solutions for IoT environments.
This thesis contributes to the architectural proposals for IoT ingestion and data processing by 1) proposing the characterization of a platform for hosting IoT workloads in the Cloud providing multi-tenant data stream processing capabilities, the interfaces over an advanced data-centric technology, including the building of a state-of-the-art infrastructure to evaluate the performance and to validate the proposed solution. 2) studying an architectural approach following the Fog paradigm that addresses some of the technical challenges found in the first contribution. The idea is to study an extension of the model that addresses some of the central challenges behind the converge of Fog and IoT. 3) Design a distributed and scalable platform to perform IoT operations in a moving data environment. The idea after study data processing in Cloud, and after study the convenience of the Fog paradigm to solve the IoT close to the Edge challenges, is to define the protocols, the interfaces and the data management to solve the ingestion and processing of data in a distributed and orchestrated manner for the Fog Computing paradigm for IoT in a moving data environment.<br>En els últims anys hi ha hagut un gran creixement del Internet of Things (IoT) i els seus protocols. La creixent difusió de dispositius electrònics amb capacitats d'identificació, computació i comunicació esta establint les bases de l’aparició de serveis altament distribuïts i del seu entorn de xarxa. L’esmentada situació implica que hi ha una creixent demanda de plataformes de processament i gestió avançada de dades per IoT. Aquestes plataformes requereixen suport per a múltiples protocols al Edge per connectivitat amb el objectes, però també necessiten d’una organització de dades interna i capacitats avançades de processament de dades per satisfer les demandes de les aplicacions i els serveis que consumeixen dades IoT. Una de les aproximacions inicials per abordar aquesta demanda és la integració entre IoT i el paradigma del Cloud computing. Hi ha molts avantatges d'integrar IoT amb el Cloud. IoT genera quantitats massives de dades i el Cloud proporciona una via perquè aquestes dades viatgin a la seva destinació. Però els models actuals del Cloud no s'ajusten del tot al volum, varietat i velocitat de les dades que genera l'IoT. Entre les noves tecnologies que sorgeixen al voltant del IoT per proporcionar un escenari nou, el paradigma del Fog Computing s'ha convertit en la més rellevant. Fog Computing es va introduir fa uns anys com a resposta als desafiaments que plantegen moltes aplicacions IoT, incloent requisits com baixa latència, operacions en temps real, distribució geogràfica extensa i mobilitat. També aquest entorn està cobert per l'arquitectura de xarxa MEC (Mobile Edge Computing) que proporciona serveis de TI i capacitats Cloud al edge per la xarxa mòbil dins la Radio Access Network (RAN) i a prop dels subscriptors mòbils. El Fog aborda casos d’us amb requisits que van més enllà de les capacitats de solucions només Cloud. La interacció entre Cloud i Fog és crucial per a l'evolució de l'anomenat IoT, però l'abast i especificació d'aquesta interacció és un problema obert. Aquesta tesi té com objectiu trobar les decisions de disseny i les tècniques adequades per construir un sistema distribuït escalable per IoT sota el paradigma del Fog Computing per a ingerir i processar dades. L'objectiu final és explorar els avantatges/desavantatges i els desafiaments en el disseny d'una solució des del Edge al Cloud per abordar les oportunitats que les tecnologies actuals i futures portaran d'una manera integrada.
Aquesta tesi descriu un enfocament arquitectònic que aborda alguns dels reptes tècnics que hi ha darrere de la convergència entre IoT, Cloud i Fog amb especial atenció a reduir la bretxa entre el Cloud i el Fog. Amb aquesta finalitat, s'introdueixen nous models i tècniques per explorar solucions per entorns IoT.
Aquesta tesi contribueix a les propostes arquitectòniques per a la ingesta i el processament de dades IoT mitjançant
1) proposant la caracterització d'una plataforma per a l'allotjament de workloads IoT en el Cloud que proporcioni capacitats de processament de flux de dades multi-tenant, les interfícies a través d'una tecnologia centrada en dades incloent la construcció d'una infraestructura avançada per avaluar el rendiment i validar la solució proposada.
2) estudiar un enfocament arquitectònic seguint el paradigma Fog que aborda alguns dels reptes tècnics que es troben en la primera contribució. La idea és estudiar una extensió del model que abordi alguns dels reptes centrals que hi ha darrere de la convergència de Fog i IoT.
3) Dissenyar una plataforma distribuïda i escalable per a realitzar operacions IoT en un entorn de dades en moviment. La idea després d'estudiar el processament de dades en el Cloud, i després d'estudiar la conveniència del paradigma Fog per resoldre els desafiaments de IoT a prop del Edge, és definir els protocols, les interfícies i la gestió de dades per resoldre la ingestió i processament de dades d’una manera més eficient
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Xu, Yunjian. "Efficiency loss in resource allocation games." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77098.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.<br>Cataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 167-176).<br>The overarching goals of this thesis are to quantify the efficiency loss due to market participant strategic behavior, and to design proper pricing mechanisms that reduce the efficiency loss. The concept of efficiency loss is intimately related to the concept of "price of anarchy," which was advanced by Koutsoupias and Papadimitriou, and compares the maximum social welfare with that achieved at a worst Nash equilibrium. This thesis focuses on the following two topics: (i) For a market with an arbitrary number of participants, how much is the Nash equilibrium close, in the sense of price of anarchy, to a social optimum? (ii) For a resource allocation/pricing mechanism, is the social welfare achieved at an economic equilibrium asymptotically optimal, as the number of market participants goes to infinity? Regarding the first topic, we quantify the efficiency loss in classical Cournot oligopoly games, where multiple oligopolists compete by choosing quantities. We also compare the total profit earned at a Cournot equilibrium to the maximum possible total profit that would be obtained if the suppliers were to collude. For the second topic, related to the efficiency in large economics, we analyze the efficiency of Kelly's proportional allocation mechanism in large-scale wireless communication systems. We study a corresponding Bayesian game in which each user has incomplete information on the state or type of the other users, and show that the social welfare achieved at a Bayes-Nash equilibrium is asymptotically optimal, as the number of users increases to infinity. Finally, for electricity delivery systems, we propose a new dynamic pricing mechanism that explicitly encourages consumers to adapt their consumption so as to offset the variability of demand on conventional units. Through a dynamic game-theoretic formulation, we show that the proposed pricing mechanism achieves social optimality asymptotically, as the number of consumers increases to infinity.<br>by Yunjian Xu.<br>Ph.D.
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Prudnikova, N. "Efficiency of Resource Potential of Enterprises." Thesis, Київський національний університет технологій та дизайну, 2017. https://er.knutd.edu.ua/handle/123456789/8445.
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Sikorska, Małgorzata, P. G. Pererva, and Kristina Kiss. "Efficiency of the enterprise resource potential." Thesis, Національний технічний університет "Харківський політехнічний інститут", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/39583.
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The economic value of the results obtained is to improve the methodological approaches to the diagnosis of the resource potential of light industry enterprises and the further development of theoretical aspects of the diagnosis of the enterprise.
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Mohamed, Omer Yusuf Adam. "Resource Allocation for Improved Performance and Resource Efficiency in Cloud Computing." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17596.
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Allocating resources for applications is attributed to cost-efficiency measures only in the light of two other factors of paramount importance, namely application performance achieved and resource efficiency associated. Achieving satisfactory performance within QoS requirements is indeed the foremost objective to attain for any given application. However, the efficiency obtained for the relevant deployed resources is equally critical as it determines to what extent a resource allocation decision was comparable to optimality, and hence may be perceived cost-efficient in that regard. Achieving high application performance comes in conflict with maintaining high resource efficiency. The compromise between the two to seek a feasible trade-off at which a cost-efficient allocation can be claimed is without doubt a complex multi-dimensional problem as it directly has to deal with an adamant prime issue that is known as performance unpredictability. It is particularly raised in resource provisioning from large-scale clouds (whose infrastructure is virtualised and shared) due to factors mainly include: heterogeneity of cloud resources, workload uncertainty, and performance interference. This thesis attempts to optimise allocation decisions made for cloud-hosted applications against the challenge of performance unpredictability by improving their resource efficiency while ensuring that each application can satisfy its performance objectives in a cost-efficient deployment. To this end, we follow a holistic approach to present our contributions through which we address each factor of the aforementioned challenge when designing allocation mechanisms to achieve optimal allocations that are efficient performance-, utilisation-, and cost-wise. Firstly, we devise a resource allocation framework that exploits and thus benefits from heterogeneity of cloud resources such that application performance is predictable despite of being running on heterogeneous resources with varying computing capacities. Then, we address the long-standing problem of resource over-provisioning in cloud datacenters in response to workload uncertainty. Finally, we design and built a QoS-aware resource controlling system that enables coordinated execution amongst multiple applications on shared resources, with which a potential performance interference can be mitigated.
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SÖDERBÄRG, KARL. "Industry 4.0 to enhance lean resource efficiency." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299625.
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This paper is a practical and empirical investigation into the relationship and overlap between the two industrial paradigms of Lean Management and Industry 4.0. This is accomplished with an in-depth case study of a goods receipt to identify Lean wastes and accompanied by a discussion on how these wastes can be eliminated by enhancing the processes and material flows with Industry 4.0 technologies. It was found that efforts to enhance a process with Industry 4.0 Technologies should be preceded by ensuring that the process can be performed in a standardized manner. After that the study recommends improved methods of data collection which enables the effective implementation of other supporting Industry 4.0 Technologies.<br>Denna uppsats är en praktisk och empirisk utredning av relationen och samspelet mellan de två industriella paradigmen Lean Management och Industri 4.0. Till grund för det för det ligger en utförlig fallstudie av en godsmottagning för att identifiera Lean slöserier och en tillhörande diskussion om hur dessa slöserier kan elimineras genom att förbättra arbetsprocesser och materialflöden med Industri 4.0 och tillhörande teknologier. Ur det uppdagades att åtgärder för göra processer mer effektiva med dessa Industri 4.0 teknologier bör föregås av att processen kan utföras på ett standardiserat vis. När det är säkerställt så är det denna studies rekommendation att fokusera på metoder och verktyg för insamling av data vilket blir den grund som möjliggör implementering av behjälpliga och automatiserande Industri 4.0 teknologier.
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Söderbärg, Karl. "Industry 4.0 to enhance lean resource efficiency." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301241.
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This paper is a practical and empirical investigation into the relationship and overlap between the two industrial paradigms of Lean Management and Industry 4.0. This is accomplished with an in-depth case study of a goods receipt to identify Lean wastes and accompanied by a discussion on how these wastes can be eliminated by enhancing the processes and material flows with Industry 4.0 technologies. It was found that efforts to enhance a process with Industry 4.0 Technologies should be preceded by ensuring that the process can be performed in a standardized manner. After that the study recommends improved methods of data collection which enables the effective implementation of other supporting Industry 4.0 Technologies.<br>Denna uppsats är en praktisk och empirisk utredning av relationen och samspelet mellan de två industriella paradigmen Lean Management och Industri 4.0. Till grund för det för det ligger en utförlig fallstudie av en godsmottagning för att identifiera Lean slöserier och en tillhörande diskussion om hur dessa slöserier kan elimineras genom att förbättra arbetsprocesser och materialflöden med Industri 4.0 och tillhörande teknologier. Ur det uppdagades att åtgärder för göra processer mer effektiva med dessa Industri 4.0 teknologier bör föregås av att processen kan utföras på ett standardiserat vis. När det är säkerställt så är det denna studies rekommendation att fokusera på metoder och verktyg för insamling av data vilket blir den grund som möjliggör implementering av behjälpliga och automatiserande Industri 4.0 teknologier.
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Atici, Kazim Baris. "Using data envelopment analysis for the efficiency and elasticity evaluation of agricultural farms." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/54354/.
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Data Envelopment Analysis (DEA) is a well-established relative efficiency measurement technique, which has been widely applied to evaluate the technical efficiency of agricultural units in different countries by focusing on different aspects of agricultural production. This research deals with the evaluation of efficiency through DEA in non-homogeneous agricultural production, where units produce a wide range of different outputs. The objectives are threefold. Firstly, we propose a novel methodological approach of integrating the production trade-offs concept of DEA into non-homogeneous agricultural efficiency evaluation to prevent the overstatement of the efficiency of specialist farms and overcome the issue of insufficient discrimination due to large number of outputs in the models. Secondly, we aim to integrate this methodological perspective to the theory of elasticity measurement on DEA frontiers. The efficient frontiers of DEA are not defined in functional forms as in the classical economic theory, therefore obtaining elasticity measures on them require different considerations. We introduce the production trade-offs to the elasticity measurement and derive the necessary models to calculate the elasticities of response in the presence of production trade-offs. As a third objective, before moving to the introduction of the trade-offs in elasticity measurement, for theoretical completeness, we first consider the elasticity measurement on DEA frontiers of constant returns-to-scale (CRS) technologies. Our proposed methodology and all the developed elasticity theory are illustrated in a real world case of Turkish agricultural sectors. We provide extensive empirical applications covering all the proposed theory and methodology. Among the results of this research, we provide an elasticity measurement framework, which enables us to calculate elasticities of response measures in both VRS and CRS technologies, with or without production tradeoffs included. We observe that the integration of production trade-offs provide better discrimination of efficiency scores compared to the models without trade-offs included. We also investigate how changing production trade-offs affect the efficiency and elasticity measures of the evaluated units.
Books on the topic "Resource efficiency and elasticity"
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Tofallis, Christopher. Resource efficiency profiling. University of Hertfordshire, Business School, 1994.
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Evanoff, Douglas Darrell. Scale elasticity and efficiency for U.S. banks. Federal Reserve Bank of Chicago, 1991.
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Flachenecker, Florian, and Jun Rentschler, eds. Investing in Resource Efficiency. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78867-8.
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Mishra, Manoranjan, Manoj Kumar Dash, Dinoj Kumar Upadhyay, and Raj Kishor Kampa. Resource Efficiency, Sustainability, and Globalization. Apple Academic Press, 2021. http://dx.doi.org/10.1201/9781003130833.
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Ghosh, Sadhan Kumar, ed. Waste Management and Resource Efficiency. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-7290-1.
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Krämer, Stefan Krämer, and Sebastian Engell Engell, eds. Resource Efficiency of Processing Plants. Wiley-VCH Verlag GmbH & Co. KGaA, 2018. http://dx.doi.org/10.1002/9783527804153.
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Bleischwitz, Raimund, Paul J. J. Welfens, and ZhongXiang Zhang, eds. International Economics of Resource Efficiency. Physica-Verlag HD, 2011. http://dx.doi.org/10.1007/978-3-7908-2601-2.
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Steinfeldt, Michael, Arnim von Gleich, Ulrich Petschow, and Rüdiger Haum. Nanotechnologies, Hazards and Resource Efficiency. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73815-2.
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M, Conway Kathryn, Rensselaer Polytechnic Institute. Lighting Research Center., and Electric Power Research Institute, eds. Commercial lighting efficiency resource book. Electric Power Research Institute, 1991.
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Blume, Stefan Alexander. Resource Efficiency in Manufacturing Value Chains. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63387-5.
Full textBook chapters on the topic "Resource efficiency and elasticity"
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Bardazzi, Rossella, and Maria Grazia Pazienza. "Demographic Shifts, Household Energy Needs and Vulnerability." In Studies in Energy, Resource and Environmental Economics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35684-1_3.
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AbstractStructural changes in the population are bound to be intertwined with the energy transition in determining the evolution of household energy consumption. Most countries are characterized by shrinking total population, very fast ageing and smaller family size. These demographic shifts could enlarge the group of vulnerable individuals who are suffering for energy poverty. Being a single parent or living alone, having an increasing number of elderly or individuals with specific needs related to illness and disability in the family, significantly increases the chances of facing energy poverty. When studying the drivers of future energy demand, demographic shifts represent a crucial factor although they are usually overlooked in the estimated long-run projections of energy use which mainly takes into account only the population size. In this chapter, we summarize how demographic change is interlinked with energy transition with an analysis of the main issues related to changes in the composition and the age structure of the population and their effects on the future paths of energy consumption in Italy. Then we focus on the vulnerability of the elderly and on its main specific drivers as the affordability of energy expenditures and the energy efficiency of buildings and equipment. Moreover, we briefly look at the consequences of limited access to energy services on the social activities of the ageing population. Finally, price and income elasticity estimations add further evidence on the role of age and generation in household energy consumption. These findings are relevant in understanding how the expected structural demographic changes may affect the future trend of energy poverty.
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Herrmann, Christoph. "Resource Efficiency." In CIRP Encyclopedia of Production Engineering. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-35950-7_6613-4.
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Hirschnitz-Garbers, Martin, Francesca Montevecchi, and André Martinuzzi. "Resource Efficiency." In Encyclopedia of Corporate Social Responsibility. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-28036-8_728.
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Herrmann, Christoph. "Resource Efficiency." In CIRP Encyclopedia of Production Engineering. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-53120-4_6613.
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Herrmann, Christoph. "Resource Efficiency." In CIRP Encyclopedia of Production Engineering. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-20617-7_6613.
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Gisi, Philip J. "Resource Efficiency." In The Dark Factory and the Future of Manufacturing. Productivity Press, 2024. http://dx.doi.org/10.4324/9781032688152-18.
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Therivel, Riki. "Resource efficiency." In Methods of Environmental and Social Impact Assessment. Routledge, 2017. http://dx.doi.org/10.4324/9781315626932-17.
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Boehm, Matthias, Arun Kumar, and Jun Yang. "Resource Heterogeneity and Elasticity." In Data Management in Machine Learning Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-031-01869-5_7.
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Busch, Timo, and Christa Liedtke. "Resource Efficiency Accounting." In Management Models for Corporate Social Responsibility. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-33247-2_33.
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Berkhout, Frans. "Aggregate resource efficiency." In Managing a Material World. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5125-2_11.
Full textConference papers on the topic "Resource efficiency and elasticity"
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Kujawa, Magdalena, Robert Kusiorowski, and Anna Gerle. "THE INFLUENCE OF CONVENTIONAL AND LOW-PRESSURE HEAT TREATMENT ON THE COURSE OF CHRYSOTILE ASBESTOS DECOMPOSITION." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024v/4.2/s17.21.
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Recycling of chrysotile asbestos materials is a global problem. Even though the materials containing asbestos have good properties like resistance to elevated temperatures, high elasticity and mechanical strength, or abrasion resistance, it has been proven to be carcinogenic and banned in over 70 countries. Standard disposal of asbestos products - storing them in appropriately designated areas (landfills) - is a risk-taking method due to the possibility of secondary pollution of the surrounding environment and the waste of natural resources. One of the popular methods of neutralisation asbestos fibres is their thermal treatment. This study aimed to investigate the effect of thermal treatment in the range 25-1000�C in conventional parameters and under reduced pressure of -0.1 and -0.5 bar on the dehydroxylation process of chrysotile. The thermal decomposition course of chrysotile studied by differential thermal analysis (DTA) and thermogravimetric measurements (TG-DTG) showed the possibility of using low pressure to increase the efficiency of the thermal treatment process.
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Liu, Xuesen, Wenbin Zhang, Xianghua Wang, Qingxi Yang, Zhe Li, and Chengyu Cai. "A Cloud Resource Efficiency Measurement Model." In 2025 10th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA). IEEE, 2025. https://doi.org/10.1109/icccbda64898.2025.11030539.
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Ebert, Thomas, Stephen Jayanathan, Laura Cuccaro, Rob Guzzo, Karsten Schischke, and David Sanchez. "Product Design Strategies for Decarbonization and Resource Efficiency." In 2024 Electronics Goes Green 2024+ (EGG). IEEE, 2024. http://dx.doi.org/10.23919/egg62010.2024.10631260.
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Zhao, Yaxuan, Haixia Cui, and Qikai Hao. "Energy-Efficiency Resource Optimization in Internet of Vehicles." In 2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP). IEEE, 2024. http://dx.doi.org/10.1109/icsp62122.2024.10743740.
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Sodré, Daniel Bougleux, Cristina Boeres, and Vinod E. F. Rebello. "Making the most of what you pay for by delaying tasks to improve overall cloud instance performance." In Simpósio em Sistemas Computacionais de Alto Desempenho. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/wscad_estendido.2022.226672.
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Resource elasticity and server consolidation have long been among two of cloud computing’s most relevant management tools. Yet, exemplified with a scientific application use case, this paper highlights how judicious scheduling of tasks can help maximize resource utilization and improve performance and costs for both users and cloud providers. Developing an efficient cloud service for DNA sequence comparisons is adopted as a motivating use case. Using the bioinformatics tool MASA that finds an optimal pair-wise sequence alignment, we propose a model for co-scheduling multiple alignments on a single cloud instance. The resulting, practically optimal, non-preemptive schedule can effectively double the throughput of MASA-based sequence alignment workflows.
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Zhang, Hang, Rongguang Wang, Jinwei Zhang, Dongdong Liu, Chao Li, and Jiahao Li. "Spatially Covariant Lesion Segmentation." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/190.
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Compared to natural images, medical images usually show stronger visual patterns and therefore this adds flexibility and elasticity to resource-limited clinical applications by injecting proper priors into neural networks. In this paper, we propose spatially covariant pixel-aligned classifier (SCP) to improve the computational efficiency and meantime maintain or increase accuracy for lesion segmentation. SCP relaxes the spatial invariance constraint imposed by convolutional operations and optimizes an underlying implicit function that maps image coordinates to network weights, the parameters of which are obtained along with the backbone network training and later used for generating network weights to capture spatially covariant contextual information. We demonstrate the effectiveness and efficiency of the proposed SCP using two lesion segmentation tasks from different imaging modalities: white matter hyperintensity segmentation in magnetic resonance imaging and liver tumor segmentation in contrast-enhanced abdominal computerized tomography. The network using SCP has achieved 23.8, 64.9 and 74.7 reduction in GPU memory usage, FLOPs, and network size with similar or better accuracy for lesion segmentation.
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Tchuigwa, Baurice Sylvain Sadjiep, Jan Krmela, Jan Pokorny, and Vladimira Krmelova. "Improved and vectorised matlab-based algorithms for serial and parallel implementation of finite element method in linear elasticity." In 23rd International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering and Information Technologies, 2024. http://dx.doi.org/10.22616/erdev.2024.23.tf212.
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This paper presents two improved algorithms for efficient sequential and parallel implementation of the Finite element method (FEM) for both linear and nonlinear boundary value problems. The proposed algorithms address some weak points, such as the overuse of for-loops and serial computing caused by dependencies in constructing fundamental expressions (global stiffness matrix, mass matrix, global force vector, etc.) resulting from the finite element method. By taking advantage of the concepts of sparse matrix representation, vectorization, and the physical architecture of modern computing resources, the proposed methods are free from mesh partitioning techniques or similar approaches and enable the use of all available CPU cores/threads without synchronization. Moreover, these algorithms are also adapted to deal with meshes involving elements of any order in both 2D and 3D. Two tests from NAFEMS benchmarks are implemented in MATLAB to verify the accuracy and stability of the proposed algorithms in both serial and parallel processing. According to serial and parallel computing results, the proposed algorithms perform better than the standard sparse assembly strategy and behave linearly with the mesh size but at a smaller rate than the latter. In parallel processing, the algorithms are also demonstrated to be accurate and achieve an efficiency of at least 60% in 2D and 70% with two cores/threads when the mesh size is greater than 10,000. Moreover, the simulations revealed that the performance gap between the proposed algorithm and the classical sparse algorithm is more pronounced in 2D than in 3D due to the increase in degrees of freedom.
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Nykytiuk, Oleksandr, Olesia Lynovytska, Innola Novykova, and Andrii Dinets. "Diagnostics of competitive potential of agricultural enterprises in Ukraine during war." In 23rd International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering and Information Technologies, 2024. http://dx.doi.org/10.22616/erdev.2024.23.tf160.
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The article provides an assessment of the Ukrainian agricultural market and determines that the total amount of losses caused to the agricultural industry as a result of the Russian invasion of Ukraine amounted to more than 8 billion USD at the end of 2022. At the same time, indirect losses of Ukrainian agriculture due to reduced production, blockade of ports, and growth in production costs are estimated at 34.25 billion USD. Due to a significant deterioration in the financial performance of agricultural enterprises in Ukraine, the article presents the authors’ algorithm for diagnosing the competitive potential of an agricultural enterprise based on the results of a study of internal factors influencing the competitiveness of agricultural enterprises, grouped into the following groups: - “technical level of production and sales of equipment”; - “state of production”; - “personnel and the extent of its use”; - “financial condition of society”; - “marketing resources”; - “economic efficiency of activity”; - “investment and innovation resources”. It has been proven that the use of elasticity models allows to take into account the influence of a significant number of factors, and elasticity can be defined as a measure of susceptibility to changes in one or more independent variables. It has been proven that the level of competitiveness of an agricultural enterprise at any given time is determined by the overall influence of interrelated factors, acting simultaneously and in different directions, enhancing or weakening the overall effective impact. It is substantiated that an agricultural enterprise must constantly respond to the demands of an unstable environment, reconfiguring and updating its resources and competencies; move through systematic problem solving, identify opportunities and threats, make quick decisions, implement productive strategies, etc.
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Zhang, Yushuqing, Kai Lu, and Wenzhe Zhang. "Summary of Resource Elasticity Trends." In 2021 International Conference on Intelligent Computing, Automation and Applications (ICAA). IEEE, 2021. http://dx.doi.org/10.1109/icaa53760.2021.00145.
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Zhou, Jie, Zhaozhong Yang, and Jingyi Zhu. "Experimental Study on In-Situ Foam Fracturing Fluid Stabilized by Novel Microbial Polysaccharide." In Asia Pacific Unconventional Resources Symposium. SPE, 2023. http://dx.doi.org/10.2118/217295-ms.
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Abstract While high working pressure and complex procedure restrict application of conventional foam fracturing, in-situ foam can overcome the limitations because it is liquid while pumping, reducing flow friction and dosage of special equipment. It gradually foams in the formation with large amount of heat released and pressure increased, improving flowback performance. Thus, this study developed an in-situ foam fracturing fluid stabilized by a novel microbial polysaccharide called diutan gum, evaluated its performance, and investigated its proppant suspension mechanism at high temperature. First, based on the foam comprehensive value, the polysaccharide stabilizer and foaming agent systems of N2 foam and CO2 foam were selected separately. Second, the self-generated N2 systems and self-generated CO2 systems were screened in terms of gas production efficiency and rate. Third, on the premise of meeting compatibility, the selected foam systems and self-generated gas systems were combined, and necessary additives were introduced to prepare in-situ N2 and in-situ CO2 foam fracturing fluid systems, respectively. The stability and foaming ability of in-situ foams were evaluated at high temperature, and the optimal ones were selected. Then, the proppant suspension performance, heat and shear resistance, and viscoelasticity of the optimal ones were evaluated at high temperature, and this study tailored a method for evaluating proppant suspension performance of the in-situ foam fracturing fluid due to its difference from the conventional ones. Finally, based on experimental data and rules, the proppant suspension mechanism of in-situ foam fracturing fluid at high temperature was revealed. The combination of diutan gum and AOS exhibited outstanding ability in enhancing the foam comprehensive value of both N2 and CO2 foam, and two kinds of CO2 foam and N2 foam systems with higher comprehensive values were selected respectively. The self-generated nitrogen and carbon dioxide systems with the highest gas production rate and efficiency were respectively selected, with the highest gas production efficiency reaching 95.9%. Thanks to these two excellent components, the in-situ N2foam volume reached 518mL which was 26 times of the base fluid of 20mL and remained 480mL within 90 minutes even at 70°C, demonstrating excellent foaming ability and foam stability. However, the stability of the in-situ CO2 foam was poor, as the foam volume dropped from 515mL to 250mL in just about 13 minutes. The in-situ N2 foam fracturing fluid obtained remarkable proppant suspension performance that with only 20mL of base fluid, it fully suspended 25mL of 70/140 mesh ceramic proppant for up to 120min, achieving proppant volume fraction as high as 55.6%. The in-situ CO2 foam could not even suspend 5mL of proppant, so it was eliminated and the in-situ N2 foam fracturing fluid was determined as the optimal system whose rheological properties was also extraordinary. After continuous shear for 2h at 70° and 170s−1, it maintained a viscosity of 59.4mPa·s, and it exhibited brilliant elasticity that its storage modulus was always greater than the loss modulus, ensuring its excellent proppant suspension performance. Ultimately, its proppant suspension mechanism was revealed in four stages. The results suggest that the in-situ foam fracturing fluid stabilized by diutan gum obtains promising applications and is supposed to be further studied.
Reports on the topic "Resource efficiency and elasticity"
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Frick, Natalie, Angela Long, Grace Relf, and Anthony Sandonato. Reimagining Energy Efficiency Resource Standards. Office of Scientific and Technical Information (OSTI), 2025. https://doi.org/10.2172/2499781.
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Hertel, Thomas, David Hummels, Maros Ivanic, and Roman Keeney. How Confident Can We Be in CGE-Based Assessments of Free Trade Agreements? GTAP Working Paper, 2003. http://dx.doi.org/10.21642/gtap.wp26.
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With the proliferation of Free Trade Agreements (FTAs) over the past decade, demand for quantitative analysis of their likely impacts has surged. The main quantitative tool for performing such analysis is Computable General Equilibrium (CGE) modeling. Yet these models have been widely criticized for performing poorly (Kehoe, 2002) and having weak econometric foundations (McKitrick, 1998; Jorgenson, 1984). FTA results have been shown to be particularly sensitive to the trade elasticities, with small trade elasticities generating large terms of trade effects and relatively modest efficiency gains, whereas large trade elasticities lead to the opposite result. Critics are understandably wary of results being determined largely by the authors’ choice of trade elasticities. Where do these trade elasticities come from? CGE modelers typically draw these elasticities from econometric work that uses time series price variation to identify an elasticity of substitution between domestic goods and composite imports (Alaouze, 1977; Alaouze, et al., 1977; Stern et al., 1976; Gallaway, McDaniel and Rivera, 2003). This approach has three problems: the use of point estimates as “truth”, the magnitude of the point estimates, and estimating the relevant elasticity. First, modelers take point estimates drawn from the econometric literature, while ignoring the precision of these estimates. As we will make clear below, the confidence one has in various CGE conclusions depends critically on the size of the confidence interval around parameter estimates. Standard “robustness checks” such as systematically raising or lowering the substitution parameters does not properly address this problem because it ignores information about which parameters we know with some precision and which we do not. A second problem with most existing studies derives from the use of import price series to identify home vs. foreign substitution, for example, tends to systematically understate the true elasticity. This is because these estimates take price variation as exogenous when estimating the import demand functions, and ignore quality variation. When quality is high, import demand and prices will be jointly high. This biases estimated elasticities toward zero. A related point is that the fixed-weight import price series used by most authors are theoretically inappropriate for estimating the elasticities of interest. CGE modelers generally examine a nested utility structure, with domestic production substitution for a CES composite import bundle. The appropriate price series is then the corresponding CES price index among foreign varieties. Constructing such an index requires knowledge of the elasticity of substitution among foreign varieties (see below). By using a fixed-weight import price series, previous estimates place too much weight on high foreign prices, and too small a weight on low foreign prices. In other words, they overstate the degree of price variation that exists, relative to a CES price index. Reconciling small trade volume movements with large import price series movements requires a small elasticity of substitution. This problem, and that of unmeasured quality variation, helps explain why typical estimated elasticities are very small. The third problem with the existing literature is that estimates taken from other researchers’ studies typically employ different levels of aggregation, and exploit different sources of price variation, from what policy modelers have in mind. Employment of elasticities in experiments ill-matched to their original estimation can be problematic. For example, estimates may be calculated at a higher or lower level of aggregation than the level of analysis than the modeler wants to examine. Estimating substitutability across sources for paddy rice gives one a quite different answer than estimates that look at agriculture as a whole. When analyzing Free Trade Agreements, the principle policy experiment is a change in relative prices among foreign suppliers caused by lowering tariffs within the FTA. Understanding the substitution this will induce across those suppliers is critical to gauging the FTA’s real effects. Using home v. foreign elasticities rather than elasticities of substitution among imports supplied from different countries may be quite misleading. Moreover, these “sourcing” elasticities are critical for constructing composite import price series to appropriate estimate home v. foreign substitutability. In summary, the history of estimating the substitution elasticities governing trade flows in CGE models has been checkered at best. Clearly there is a need for improved econometric estimation of these trade elasticities that is well-integrated into the CGE modeling framework. This paper provides such estimation and integration, and has several significant merits. First, we choose our experiment carefully. Our CGE analysis focuses on the prospective Free Trade Agreement of the Americas (FTAA) currently under negotiation. This is one of the most important FTAs currently “in play” in international negotiations. It also fits nicely with the source data used to estimate the trade elasticities, which is largely based on imports into North and South America. Our assessment is done in a perfectly competitive, comparative static setting in order to emphasize the role of the trade elasticities in determining the conventional gains/losses from such an FTA. This type of model is still widely used by government agencies for the evaluation of such agreements. Extensions to incorporate imperfect competition are straightforward, but involve the introduction of additional parameters (markups, extent of unexploited scale economies) as well as structural assumptions (entry/no-entry, nature of inter-firm rivalry) that introduce further uncertainty. Since our focus is on the effects of a PTA we estimate elasticities of substitution across multiple foreign supply sources. We do not use cross-exporter variation in prices or tariffs alone. Exporter price series exhibit a high degree of multicolinearity, and in any case, would be subject to unmeasured quality variation as described previously. Similarly, tariff variation by itself is typically unhelpful because by their very nature, Most Favored Nation (MFN) tariffs are non-discriminatory in nature, affecting all suppliers in the same way. Tariff preferences, where they exist, are often difficult to measure – sometimes being confounded by quantitative barriers, restrictive rules of origin, and other restrictions. Instead we employ a unique methodology and data set drawing on not only tariffs, but also bilateral transportation costs for goods traded internationally (Hummels, 1999). Transportation costs vary much more widely than do tariffs, allowing much more precise estimation of the trade elasticities that are central to CGE analysis of FTAs. We have highly disaggregated commodity trade flow data, and are therefore able to provide estimates that precisely match the commodity aggregation scheme employed in the subsequent CGE model. We follow the GTAP Version 5.0 aggregation scheme which includes 42 merchandise trade commodities covering food products, natural resources and manufactured goods. With the exception of two primary commodities that are not traded, we are able to estimate trade elasticities for all merchandise commodities that are significantly different form zero at the 95% confidence level. Rather than producing point estimates of the resulting welfare, export and employment effects, we report confidence intervals instead. These are based on repeated solution of the model, drawing from a distribution of trade elasticity estimates constructed based on the econometrically estimated standard errors. There is now a long history of CGE studies based on SSA: Systematic Sensitivity Analysis (Harrison and Vinod, 1992; Wigle, 1991; Pagon and Shannon, 1987) Ho
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Dalhammar, Carl, Erika Machacek, Anja Bundgaard, Kristina Overgaard Zacho, and Arne Remmen. Addressing resource efficiency through the Ecodesign Directive. Nordic Council of Ministers, 2014. http://dx.doi.org/10.6027/tn2014-511.
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Author, Not Given. Guide to Resource Planning with Energy Efficiency. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/1219675.
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none,. Energy Efficiency as a Resource Regional Reports Introduction. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1218527.
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Van Buskirk, Robert. Estimating Energy Efficiency Technology Adoption Curve Elasticity with Respect to Government and Utility Deployment Program Indicators. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1164376.
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Steinberg, D., and O. Zinaman. State Energy Efficiency Resource Standards: Design, Status, and Impacts. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1134131.
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Glatt, Sandy, Ryan Harry, and Garrett Shields. Energy Efficiency as a Resource Regional Report: Midwest Region. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1218523.
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Glatt, Sandy, Ryan Harry, and Garrett Shields. Energy Efficiency as a Resource Regional Report: Northeast Region. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1218524.
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Glatt, Sandy, Ryan Harry, and Garrett Shields. Energy Efficiency as a Resource Regional Report: South Region. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1218525.
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